Occurence of natural disasters in the US
Milica Pajkic, Martina Heidemann
2023-02-17
Background
Climate change is one of the biggest challenges facing humanity today resulting among other effects in more frequent and severe weather events. The Federal Emergency Management Agency (FEMA) is part of Homeland Security in the USA and responsible for coordinating the response to disasters and emergencies, both natural and man-made. FEMA provides support to state and local governments, as well as to individuals affected by disasters, by offering financial assistance, providing temporary housing, and assisting with recovery efforts. The agency also plays a key role in disaster preparedness and risk reduction through programs that help communities develop plans and take steps to reduce the impact of future disasters.
Description of data set(s)
FEMA provides various data sets on disasters that occurred in the past, some of them going back to the 1960s. For our project we merged two data sets from FEMA and enriched them with additional information like geographical data (e.g. longitude, latitude) and population size per state from Wikipedia. The first data set from FEMA contains for example information on the type of disaster (fire, flooding, etc.), the state in which the disaster occurred and the dates when it occurred. From the second data set, we pulled information on the amount of damage each disaster caused, measured in amount of money. Since the second data set only goes back to 2002, we decided to do our analysis in the time frame of the past 20 years.
After merging and cleaning the data from the four sources, our final data set to do the analysis on looked like this:
| Disaster# | Type | County | State | Latitude | Longitude | Damage | Approved | Repair | Population | IncomeCapita | DisasterBegin | DisasterEnd | Duration |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1971 | Severe Storm | Marshall | Alabama | 34.3670 | -86.3066 | 468614.48 | 116003.84 | 101089.45 | 96137 | 20382 | 2011-04-15 | 2011-05-31 | 46 days |
| 4655 | Flood | Park | Montana | 45.4884 | -110.5267 | 2901.34 | 12532.99 | 11078.99 | 16513 | 24611 | 2022-06-10 | 2022-07-05 | 25 days |
| 4637 | Tornado | Cheatham | Tennessee | 36.2612 | -87.0868 | 7753.23 | 14653.23 | 6344.23 | 40539 | 23459 | 2021-12-10 | 2021-12-11 | 1 days |
| 4633 | Tornado | Jackson | Arkansas | 35.5992 | -91.2145 | 199.50 | 199.50 | 0.00 | 16908 | 15609 | 2021-12-10 | 2021-12-11 | 1 days |
| 4630 | Tornado | Lyon | Kentucky | 37.0191 | -88.0833 | 0.00 | 0.00 | 0.00 | 8226 | 22123 | 2021-12-10 | 2021-12-11 | 1 days |
| 4618 | Hurricane | Bucks | Pennsylvania | 40.3370 | -75.1069 | 92390.42 | 52031.76 | 42999.73 | 627668 | 37466 | 2021-08-31 | 2021-09-05 | 5 days |
Exploratory Data Analysis
Relative frequency of disaster types
Displaying the cumulative frequencies of each disaster type relative to each other, we can learn from the stacked bar chart that “severe storms” are by far the commonest disaster type, followed by hurricanes and biological disasters.
Distribution of disaster types over time
Various insights can be gained from the time plot below. For example, it looks like for example severe storms happen quite frequently in general except for the years of approximately 2013-2015 and 2017/2018-ish. Furthermore, only one volcanic eruption and one severe ice storm was recorded in the displayed time period. Dam or Levee breaks and biological disasters did not occur between 2000 and 2023. We could hypothesize that fires seemed to last longer in years previous to about 2013 compared to afterwards - maybe due to more efficient ways that were developed to extinguish them. However, in this plot, the duration of almost 500 disasters are shown which might overlap. Since using 500 different colors for each individual disaster might not help much, we would switch to a different way of showing this information, for example an interactive graphic with Shiny.
Duration per disaster type
Exploring the disaster types a little bit further, we can detect in the boxplot below that fires show the largest variation in terms of duration. It is also the one with the highest median (speaking of duration). Next to the natural catastroph fire, earthquakes have the second highest Dam or Levee breaks, volcanic eruptions, tornados and severe ice storms are amongst the disasters with the shortest durations.
Damage per state
To analyse the data on damage, we first took a look at the distribution of the data points. The histogram indicated a right skewed distribution.
Also, the difference between the individual damage amounts are quite large which makes it hard to work with. Therefore, we took the logarithm of the data, which resulted in displaying a normal distribution:
With the transformed data, we could generate a plot showing the damage disasters have cause per state in the US over the past 20 years:
## function (x, ...)
## {
## if (need_screenshot(x, ...)) {
## html_screenshot(x)
## }
## else {
## UseMethod("knit_print")
## }
## }
## <bytecode: 0x11b563930>
## <environment: namespace:knitr>
g <- ggplot(map_dam) +
geom_polygon_interactive(
color='black',
aes(x = long, y = lat, group = group, fill = damage2,
tooltip=sprintf("%s<br/>%s",region,damage))) +
labs(x = 'Longitude', y = 'Latitude', fill = '$ damage') +
coord_quickmap() +
# scale_fill_gradient(limits = c(min(map_dam$damage2), max(map_dam$damage2)),
# breaks = c(min(map_dam$damage2), max(map_dam$damage2)),
# labels = c("Low", "High"), na.value = "grey50") +
hrbrthemes::theme_ipsum() +
colormap::scale_fill_colormap(
colormap=colormap::colormaps$hot, reverse = T) +
labs(title='Log. Damage in the USA',
caption='Source: FEMA.')
widgetframe::frameWidget(ggiraph(code=print(g)))Population per state
The following map shows the population per state. Similar to above, we are using the log-transformed data.
Damage vs. approved
Hier will ich zwei Volcanic ausschliessen
Damage muss ich logarithmieren
Even with the changes in bin we can see a stark right skewedness. The first step to change right skewedness is to log-transform it.
With this caculation: damage - approved it is visible where the cost of damage has been adequately given and where the monetary help has come short. If the difference is negative, then more money has been approved than there is damage. If it is positive, then the allocation of approved money is smaller than the damage and therefore, not enough money has been given for help.
In the histogram it is clearly seen, that
diff_approved <- data.frame(DisasterN = df.prep.5$`Disaster#`,
Type = df.prep.5$Type,
Duration = df.prep.5$Duration,
Damage = df.prep.5$Damage,
Approved = df.prep.5$Approved)
diff_approved$difference <- diff_approved$Damage - diff_approved$Approved
summary(diff_approved$difference)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -53389 -550 0 216233 3599 80102211hist.df <- data.frame(Damage = df.prep.5$Damage,
Approved = df.prep.5$Approved)
hist.df %>%
pivot_longer(everything()) %>%
ggplot(aes(x = value, fill = name)) +
geom_histogram(position = "identity", alpha = 0.5) +
scale_x_continuous(limits = c(0, 300000)) +
scale_y_continuous(limits = c(0, 70))
hist.app.log.df <- data.frame(Damage = log(df.prep.5$Damage),
Approved = log(df.prep.5$Approved))
hist.app.log.df %>%
pivot_longer(everything()) %>%
ggplot(aes(x = value, fill = name)) +
geom_histogram(position = "identity", alpha = 0.5)
boxplot.approved.df <- data.frame(Damage = log(df.prep.5$Damage),
Approved = log(df.prep.5$Approved),
Type = df.prep.5$Type)
boxplot.approved.num <- boxplot.approved.df %>%
filter_if(~is.numeric(.), all_vars(!is.infinite(.)))
b.app.inf <- boxplot.approved.df %>%
pivot_longer(Damage:Approved, names_to = "Names", values_to = "values") %>%
ggplot(aes(y = values, x = Type, fill = Names))+
geom_boxplot()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+
labs(fill = "")
b.app <- boxplot.approved.num %>%
pivot_longer(Damage:Approved, names_to = "Names", values_to = "values") %>%
ggplot(aes(y = values, x = Type, fill = Names))+
geom_boxplot()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))+
labs(fill = "")
label_size <- 10 # set the size of the labels
label_top <- "<span style='font-size: {size}px;'>With Infinite Numbers</span>"
label_bottom <- "<span style='font-size: {size}px;'>Without Infinite Numbers</span>"
ggarrange(b.app.inf, b.app,
labels = c("With Infinite Numbers", "Without Infinite Number"),
font.label = list(size = 10), hjust = -0.1,
ncol = 1, nrow = 2)
Approved and actually used (repair)
repair.short.df <- data.frame(Approved = df.prep.5$Approved,
Repair = df.prep.5$Repair)
summary(repair.short.df)## Approved Repair
## Min. : 0 Min. : 0
## 1st Qu.: 0 1st Qu.: 0
## Median : 4765 Median : 1224
## Mean : 79661 Mean : 59403
## 3rd Qu.: 21986 3rd Qu.: 14558
## Max. :10854341 Max. :7422124 repair.short.df %>%
pivot_longer(everything()) %>%
ggplot(aes(x = value, fill = name)) +
geom_histogram(position = "identity", alpha = 0.5) +
scale_x_continuous(limits = c(0, 300000)) +
scale_y_continuous(limits = c(0, 70))
repair.log.df <- data.frame(Approved = log(df.prep.5$Approved),
Repair = log(df.prep.5$Repair))
repair.log.df %>%
pivot_longer(everything()) %>%
ggplot(aes(x = value, fill = name)) +
geom_histogram(position = "identity", alpha = 0.5)
boxplot.repair.df <- data.frame(ApprovedLog = log(df.prep.5$Approved),
RepairLog = log(df.prep.5$Repair),
Type = df.prep.5$Type)
boxplot.repair.num.df <- boxplot.repair.df %>%
filter_if(~is.numeric(.), all_vars(!is.infinite(.)))
b.rep.inf <- boxplot.repair.num.df %>%
pivot_longer(ApprovedLog:RepairLog, names_to = "Names", values_to = "values") %>%
ggplot(aes(y = values, x = Type, fill = Names))+
geom_boxplot() +
facet_wrap(~Type, scale="free")+
ggtitle('Approved and Repair Amount logarthmized without Inf Rows')
b.rep.inf + theme(
plot.title = element_text(size=12, face="bold.italic"),
axis.text.x=element_blank())
b.rep <- boxplot.repair.df %>%
pivot_longer(ApprovedLog:RepairLog, names_to = "Names", values_to = "values") %>%
ggplot(aes(y = values, x = Type, fill = Names))+
geom_boxplot() +
facet_wrap(~Type, scale="free")+
ggtitle('Approved and Repair Amount logarthmized with Inf Rows')
b.rep+
theme(
plot.title = element_text(color = 'red',size=12, face="bold.italic"),
axis.text.x=element_blank())
# ggarrange(b.rep.inf, b.rep,
# labels = c("With Infinite Numbers", "Without Infinite Number"),
# ncol = 1, nrow = 2)Frequency of Disaster Types by Country
DF2 <- df.prep.5 %>%
select(County, Longitude, Latitude, State)
df.group.county <- df.prep.5 %>%
group_by(County, State, Type) %>%
summarize(number_sightings = n())
df.county.2 <- left_join(df.group.county, DF2, by = c("County", "State")) %>%
rename(state = State)
df.county.2 <- df.county.2[!duplicated(df.county.2), ]
#write.csv(df.group.county, "df.group.states.csv")
library(usmap)
library(ggplot2)
plot_usmap(regions = "counties") +
labs(title = "US Counties",
subtitle = "This is a blank map of the counties of the United States.") +
theme(panel.background = element_rect(color = "black", fill = "lightblue"))
plot_usmap(data = df.county.2, values = "number_sightings", color = "red") +
scale_fill_continuous(
low = "white", high = "red", name = "Number of Sightings", label = scales::comma
) + theme(legend.position = "right")
# plot_usmap(data = df.county.2, values = "number_sightings", color = "red") +
# scale_fill_continuous(
# low = "blue", high = "red", name = "Number of Sightings", label = scales::comma
# ) + theme(legend.position = "right") +
# facet_wrap(~ Type, ncol = 2)
#
# plot_usmap(data = df.county.2, values = "number_sightings", color = "red", include = c("all")) +
# scale_fill_continuous(
# low = "blue", high = "red", name = "Number of Sightings", label = scales::comma
# ) + theme(legend.position = "right") +
# facet_wrap(~ Type, ncol = 2)Model
The goal of this model fitting chapter is to see if the linear regression is appropriate tool to predict/explain the damage amount and state.
The sum of the damage across one state shows a light right skewedness. Therefore, we performed a log transformation. Now it is more of a normal distribution.
df.group.damage <- df.prep.5 %>%
group_by(State) %>%
summarise(across(c(Damage, IncomeCapita, Duration, Population), sum, na.rm = TRUE))ggplot(data = df.group.damage,
mapping = aes(x = Damage, fill = '')) +
geom_histogram(show.legend = FALSE)+
labs(x = 'Damage', y = 'Count') +
scale_fill_manual(values = c('salmon4')) +
theme(axis.text=element_text(size=12),
axis.title=element_text(size=18,face="bold"))
ggplot(data = df.group.damage,
mapping = aes(x = log(Damage), fill = '')) +
geom_histogram(show.legend = FALSE)+
labs(x = 'Damage (log)', y = 'Count') +
scale_fill_manual(values = c('mistyrose3'))+
theme(axis.text=element_text(size=12),
axis.title=element_text(size=18,face="bold"))
model <- lm(Damage ~ Population + State, data = df.group.damage)
summary(model)##
## Call:
## lm(formula = Damage ~ Population + State, data = df.group.damage)
##
## Residuals:
## ALL 51 residuals are 0: no residual degrees of freedom!
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.254e+05 NaN NaN NaN
## Population 8.512e-01 NaN NaN NaN
## StateAlaska -1.823e+05 NaN NaN NaN
## StateArizona 7.951e+04 NaN NaN NaN
## StateArkansas 4.121e+04 NaN NaN NaN
## StateCalifornia -2.553e+07 NaN NaN NaN
## StateColorado -8.634e+05 NaN NaN NaN
## StateConnecticut -1.861e+06 NaN NaN NaN
## StateDelaware -9.730e+05 NaN NaN NaN
## StateDistrict of Columbia -1.015e+06 NaN NaN NaN
## StateFlorida 2.031e+06 NaN NaN NaN
## StateGeorgia -1.358e+05 NaN NaN NaN
## StateHawaii 8.988e+07 NaN NaN NaN
## StateIdaho 1.142e+05 NaN NaN NaN
## StateIllinois -7.148e+05 NaN NaN NaN
## StateIndiana -7.276e+05 NaN NaN NaN
## StateIowa 1.003e+05 NaN NaN NaN
## StateKansas 1.922e+05 NaN NaN NaN
## StateKentucky 2.259e+06 NaN NaN NaN
## StateLouisiana -1.219e+06 NaN NaN NaN
## StateMaine -2.164e+05 NaN NaN NaN
## StateMaryland -1.844e+06 NaN NaN NaN
## StateMassachusetts -2.638e+06 NaN NaN NaN
## StateMichigan -1.297e+06 NaN NaN NaN
## StateMinnesota 9.524e+04 NaN NaN NaN
## StateMississippi 1.416e+06 NaN NaN NaN
## StateMissouri -2.453e+06 NaN NaN NaN
## StateMontana 4.964e+04 NaN NaN NaN
## StateNebraska 1.023e+05 NaN NaN NaN
## StateNevada 8.954e+04 NaN NaN NaN
## StateNew Hampshire -6.910e+05 NaN NaN NaN
## StateNew Jersey -3.816e+06 NaN NaN NaN
## StateNew Mexico 8.470e+05 NaN NaN NaN
## StateNew York -4.593e+06 NaN NaN NaN
## StateNorth Carolina -4.627e+05 NaN NaN NaN
## StateNorth Dakota 4.940e+05 NaN NaN NaN
## StateOhio -1.747e+06 NaN NaN NaN
## StateOklahoma 5.055e+05 NaN NaN NaN
## StateOregon 7.436e+05 NaN NaN NaN
## StatePennsylvania -3.838e+06 NaN NaN NaN
## StateRhode Island -2.535e+04 NaN NaN NaN
## StateSouth Carolina 2.105e+06 NaN NaN NaN
## StateSouth Dakota 8.922e+05 NaN NaN NaN
## StateTennessee -1.452e+06 NaN NaN NaN
## StateTexas -3.988e+06 NaN NaN NaN
## StateUtah -1.843e+05 NaN NaN NaN
## StateVermont -4.269e+04 NaN NaN NaN
## StateVirginia 3.550e+05 NaN NaN NaN
## StateWashington -2.381e+05 NaN NaN NaN
## StateWest Virginia 1.669e+06 NaN NaN NaN
## StateWisconsin 1.416e+05 NaN NaN NaN
## StateWyoming NA NA NA NA
##
## Residual standard error: NaN on 0 degrees of freedom
## Multiple R-squared: 1, Adjusted R-squared: NaN
## F-statistic: NaN on 50 and 0 DF, p-value: NAModel 2
In this Chapter we want to see, if the amount of Damage can be predicted with the given data points.
H1: With a higher income per capita, the damage will be lower.
The reason being, that with higher income capita, the preparation and precaution for natural disaster are higher. For one, there is no monetary strain like in other counties with less income per capita.
H2: The damage will be lower, depending which natural catastrophe is happening.
First, we will need to see the distribution of the important variables. It appears, that damage and income per capita needs to be logarithmized. So we logarithimized it.
The scatter plot indicates that there is a positive relationship between income per capita and damage.
To see if the chosen variables have an influence on damage a testing was done (drop1). The model.full indicates that only log.income, Type and Duration have relevant effects on the dependent variable damage.
ggplot(data = df.prep.5,
mapping = aes(x = log(Damage), fill = '')) +
geom_histogram(show.legend = FALSE)+
labs(x = 'Damage (log)', y = 'Count') +
scale_fill_manual(values = c('mistyrose3'))+
theme(axis.text=element_text(size=12),
axis.title=element_text(size=18,face="bold"))
ggplot(data = df.prep.5,
mapping = aes(x = IncomeCapita, fill = '')) +
geom_histogram(show.legend = FALSE)+
labs(x = 'Income', y = 'Count') +
scale_fill_manual(values = c('lightblue2'))+
theme(axis.text=element_text(size=12),
axis.title=element_text(size=18,face="bold"))
ggplot(data = df.prep.5,
mapping = aes(x = log(IncomeCapita), fill = '')) +
geom_histogram(show.legend = FALSE)+
labs(x = 'log. Income', y = 'Count') +
scale_fill_manual(values = c('mistyrose3'))+
theme(axis.text=element_text(size=12),
axis.title=element_text(size=18,face="bold"))
plot(df.prep.5$Damage, df.prep.5$IncomeCapita)
plot(log(df.prep.5$Damage), log(df.prep.5$IncomeCapita))
ggplot(df.prep.5, aes(log(IncomeCapita),log(Damage))) +
geom_point() +
geom_smooth(method = "lm", se = FALSE)
Linear Regression
df.model <- df.prep.5
df.model$log.damage <- log(df.model$Damage)
df.model$log.income <- log(df.model$IncomeCapita)
#
df.model <- df.model[!is.na(df.model$log.damage) & is.finite(df.model$log.damage), ]
#
model <- lm(log.damage ~ log.income, data = na.omit(df.model))
summary(model)##
## Call:
## lm(formula = log.damage ~ log.income, data = na.omit(df.model))
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.2833 -1.7712 -0.1211 1.6129 8.7048
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.5667 5.2192 -0.683 0.4949
## log.income 1.2822 0.5184 2.473 0.0139 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.421 on 309 degrees of freedom
## Multiple R-squared: 0.01941, Adjusted R-squared: 0.01624
## F-statistic: 6.117 on 1 and 309 DF, p-value: 0.01392model.full <- lm(log.damage ~ log.income + State+ Type+ Population+ Duration, data = na.omit(df.model))
summary(model.full)##
## Call:
## lm(formula = log.damage ~ log.income + State + Type + Population +
## Duration, data = na.omit(df.model))
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.364 -1.379 0.000 1.358 6.059
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.882e+00 7.277e+00 -0.671 0.5029
## log.income 1.451e+00 7.046e-01 2.060 0.0405 *
## StateAlaska -1.311e+00 1.723e+00 -0.761 0.4473
## StateArkansas 9.686e-01 9.610e-01 1.008 0.3145
## StateCalifornia 8.646e-01 1.401e+00 0.617 0.5377
## StateColorado -1.704e+00 1.760e+00 -0.969 0.3337
## StateConnecticut -4.361e-01 1.397e+00 -0.312 0.7551
## StateDelaware -1.544e+00 2.424e+00 -0.637 0.5246
## StateFlorida 1.421e-01 8.456e-01 0.168 0.8667
## StateGeorgia -8.184e-01 9.437e-01 -0.867 0.3867
## StateHawaii -4.165e-01 1.550e+00 -0.269 0.7884
## StateIllinois 3.577e-01 9.325e-01 0.384 0.7016
## StateIndiana -3.766e-01 9.327e-01 -0.404 0.6867
## StateIowa -4.459e-01 1.331e+00 -0.335 0.7379
## StateKansas 4.305e-02 1.475e+00 0.029 0.9767
## StateKentucky -9.493e-02 8.535e-01 -0.111 0.9115
## StateLouisiana 1.670e-01 8.970e-01 0.186 0.8524
## StateMaine -1.158e+00 1.760e+00 -0.658 0.5111
## StateMaryland 1.438e+00 1.782e+00 0.807 0.4205
## StateMassachusetts -9.197e-01 1.255e+00 -0.733 0.4645
## StateMichigan 4.720e-01 1.504e+00 0.314 0.7539
## StateMinnesota -1.209e+00 1.336e+00 -0.905 0.3662
## StateMississippi 9.258e-01 7.989e-01 1.159 0.2476
## StateMissouri -3.151e-01 9.981e-01 -0.316 0.7525
## StateMontana -1.686e+00 1.797e+00 -0.938 0.3492
## StateNebraska -2.212e+00 1.487e+00 -1.487 0.1382
## StateNevada 5.371e+00 2.382e+00 2.254 0.0250 *
## StateNew Hampshire -1.793e+00 1.353e+00 -1.325 0.1864
## StateNew Jersey -8.625e-01 1.095e+00 -0.788 0.4317
## StateNew Mexico 5.113e+00 2.382e+00 2.147 0.0328 *
## StateNew York -1.380e+00 9.197e-01 -1.501 0.1346
## StateNorth Carolina -2.630e-01 1.084e+00 -0.243 0.8086
## StateNorth Dakota -7.434e-01 1.839e+00 -0.404 0.6863
## StateOhio -4.104e-02 1.001e+00 -0.041 0.9673
## StateOklahoma -1.962e-01 9.490e-01 -0.207 0.8364
## StateOregon -5.421e-02 1.755e+00 -0.031 0.9754
## StatePennsylvania -7.499e-03 1.166e+00 -0.006 0.9949
## StateRhode Island 2.189e-01 2.450e+00 0.089 0.9289
## StateSouth Carolina 1.276e+00 1.321e+00 0.965 0.3353
## StateSouth Dakota -1.277e+00 1.369e+00 -0.933 0.3518
## StateTennessee -7.755e-01 9.151e-01 -0.847 0.3975
## StateTexas -1.098e-01 8.562e-01 -0.128 0.8980
## StateVermont -1.653e+00 2.395e+00 -0.690 0.4907
## StateVirginia -6.829e-01 1.150e+00 -0.594 0.5532
## StateWashington 8.993e-02 1.753e+00 0.051 0.9591
## StateWest Virginia -7.573e-01 8.890e-01 -0.852 0.3951
## StateWisconsin 4.020e-01 1.478e+00 0.272 0.7859
## StateWyoming -2.834e+00 2.434e+00 -1.165 0.2452
## TypeEarthquake 1.446e+00 2.973e+00 0.486 0.6272
## TypeFire 1.291e+00 2.933e+00 0.440 0.6603
## TypeFlood -2.039e-01 2.692e+00 -0.076 0.9397
## TypeHurricane -4.446e-01 2.707e+00 -0.164 0.8697
## TypeOther 3.339e+00 3.645e+00 0.916 0.3606
## TypeSevere Ice Storm -9.198e-01 3.163e+00 -0.291 0.7715
## TypeSevere Storm -5.954e-01 2.674e+00 -0.223 0.8240
## TypeTornado -2.885e+00 2.785e+00 -1.036 0.3014
## TypeVolcanic Eruption 7.260e+00 3.827e+00 1.897 0.0590 .
## Population 1.587e-07 2.442e-07 0.650 0.5165
## Duration 1.327e-02 6.997e-03 1.897 0.0590 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.302 on 252 degrees of freedom
## Multiple R-squared: 0.2769, Adjusted R-squared: 0.1105
## F-statistic: 1.664 on 58 and 252 DF, p-value: 0.004167drop1(model.full, test = 'F')## Single term deletions
##
## Model:
## log.damage ~ log.income + State + Type + Population + Duration
## Df Sum of Sq RSS AIC F value Pr(>F)
## <none> 1335.5 571.21
## log.income 1 22.480 1358.0 574.40 4.2418 0.04047 *
## State 46 207.012 1542.5 524.03 0.8492 0.74329
## Type 9 116.823 1452.3 579.29 2.4493 0.01090 *
## Population 1 2.236 1337.7 569.73 0.4220 0.51654
## Duration 1 19.064 1354.5 573.62 3.5974 0.05902 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1model.right <- lm(log.damage ~ log.income + Type+ Duration, data = na.omit(df.model))
summary(model.right)##
## Call:
## lm(formula = log.damage ~ log.income + Type + Duration, data = na.omit(df.model))
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.960 -1.570 -0.078 1.551 5.864
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.750439 5.472425 0.320 0.7493
## log.income 0.837698 0.497469 1.684 0.0932 .
## TypeEarthquake 1.007025 2.474533 0.407 0.6843
## TypeFire 1.504898 2.482205 0.606 0.5448
## TypeFlood -0.929765 2.316326 -0.401 0.6884
## TypeHurricane -0.813160 2.297781 -0.354 0.7237
## TypeOther 3.478853 3.221237 1.080 0.2810
## TypeSevere Ice Storm -1.994636 2.789519 -0.715 0.4751
## TypeSevere Storm -1.207145 2.284732 -0.528 0.5976
## TypeTornado -3.328925 2.388800 -1.394 0.1645
## TypeVolcanic Eruption 6.932481 3.280384 2.113 0.0354 *
## Duration 0.009687 0.006022 1.609 0.1088
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.278 on 299 degrees of freedom
## Multiple R-squared: 0.1602, Adjusted R-squared: 0.1293
## F-statistic: 5.184 on 11 and 299 DF, p-value: 1.822e-07Fitted Values
fitted.model <- fitted(model)
str(fitted.model)## Named num [1:311] 9.16 9.4 9.34 8.81 9.94 ...
## - attr(*, "names")= chr [1:311] "1" "2" "3" "4" ...plot(log.damage ~ log.income, data = df.model,
main = "Model 'model'",
col = "pink4")
# points(fitted.model ~ log.income,
# col = "lightblue4",
# pch = 19,
# data = df.model)
# abline(model, col = "red4")df.sub <- df.model[which(!is.na(fitted.model)), ]
# Create plot with both observed and fitted values
plot(log.damage ~ log.income, data = df.sub,
main = "Model 'model'",
col = "pink4")
points(fitted.model ~ log.income,
col = "lightblue4",
pch = 19,
data = df.sub)
abline(model, col = "red4")
# df.plot <- data.frame(log.damage = df.model$log.damage, log.income = df.model$log.income, fitted = fitted.model)
#
# # Plot the observed and fitted values
# plot(log.damage ~ log.income, data = df.plot, main = "Model 'model'", col = "pink4")
# points(fitted ~ log.income, data = df.plot, col = "lightblue4", pch = 19)
# abline(model, col = "red4")Chapter of choice
For the chapter of choice we have chosen the shiny dashboard application. The focus lies on the exploratory analysis and to make it interactive for users. @ MARTINA: in the folder shiny there are the first tries
For every analysis some kind of outlier detection is a way to see if the data has some structure. The way this works, multiple variables are given and from these groups are being formed. The goal is to have big differences between the formed groups. However, within group difference should be small.
#Dataframe
df.outlier.0 <- data.frame(Approved = df.prep.5$Approved,
Repair = df.prep.5$Repair,
income = df.prep.5$IncomeCapita,
population = df.prep.5$Population,
damage = df.prep.5$Damage)
df.outlier.1 <- data.frame(repair = df.outlier.0$Repair,
income = df.outlier.0$income)
plot(df.outlier.1)
Clustering the two variables income and repair
When we scale the data we get one big cluster. By examining, after the initial clustering, we can see that the elbow is at 2 or 5. The further analysis with plots of the clusters and silhouette plot gives the indication that two clusters are the better solution. This means
#prep the data
datas <- scale(df.outlier.1, center = FALSE, scale = TRUE)
datas <- na.omit(datas)
boxplot(datas)
plot(datas)
dists <- dist(datas)km <- kmeans(datas, centers = 3, nstart = 10)
groups_km <- km$cluster
groups_km## [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [112] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [149] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [223] 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [260] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [297] 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [334] 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [371] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [408] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [445] 1cluster_size <- cbind(sum(groups_km == 1), sum(groups_km == 2),
sum(groups_km == 3))
cluster_size## [,1] [,2] [,3]
## [1,] 440 4 1plot(datas, pch = groups_km, col=groups_km, lwd=2)
legend("topright", legend = 1:3, pch = 1:3, col=1:3, bty="n")
reps <- rep(0, 6)
for (i in 1:6) reps[i] <- sum(kmeans(datas, centers = i, nstart = 20)$withinss)
par(mfrow = c(1,1))
plot(1:6, reps, type = "b", xlab = "Number of groups", ylab = "Sum of squares")
text(3, 120, "Elbow point signifies how many \ngroups there could be", col = "red", cex = 1.08, pos = 4)
km2 <- kmeans(datas, centers = 2, nstart = 10)
groups_km2 <- km2$cluster
groups_km2## [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [38] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [75] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [149] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [186] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [223] 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [260] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [297] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [334] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [371] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [408] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## [445] 2cluster_size2 <- cbind(sum(groups_km2 == 1), sum(groups_km2 == 2))
cluster_size2## [,1] [,2]
## [1,] 2 443plot(datas, pch = groups_km2, col=groups_km2, lwd=2)
legend("topright", legend = 1:2, pch = 1:2, col=1:2, bty="n")
plot(silhouette(groups_km, dists), color='red3', main = "")
km5 <- kmeans(datas, centers = 5, nstart = 10)
groups_km5 <- km5$cluster
groups_km5## [1] 3 3 3 3 3 5 2 5 3 3 3 3 5 5 3 5 3 5 3 3 3 3 3 3 3 3 3 3 5 5 5 3 5 3 3 3 3
## [38] 3 3 5 5 3 3 3 5 5 3 3 3 3 5 5 3 3 5 3 3 3 5 2 5 5 5 3 3 3 5 3 3 5 5 3 5 3
## [75] 5 3 3 5 3 3 3 3 3 5 5 3 5 3 5 3 3 5 3 3 3 3 5 3 3 5 5 5 3 3 3 5 3 5 5 5 5
## [112] 3 3 3 5 3 5 5 5 3 3 5 5 5 5 3 3 5 5 3 3 5 3 3 3 5 3 3 3 5 5 5 5 3 5 5 3 3
## [149] 5 3 3 5 3 3 5 3 3 3 3 3 3 3 5 5 5 3 3 5 3 5 3 3 5 3 3 3 3 3 3 5 3 3 5 5 5
## [186] 5 3 3 3 2 5 3 3 3 3 3 3 3 3 5 3 3 3 3 3 3 3 3 3 3 5 3 3 3 3 5 5 3 3 5 5 3
## [223] 3 3 3 3 3 5 3 5 5 4 5 5 5 5 3 5 3 3 3 5 3 3 3 3 5 3 3 3 3 3 5 3 5 3 3 3 5
## [260] 3 3 5 5 3 5 5 5 3 5 3 5 5 3 3 3 1 5 3 3 5 3 3 3 3 3 3 3 3 5 3 3 3 3 3 3 3
## [297] 2 3 3 3 3 3 3 5 3 3 3 3 3 3 3 5 3 3 3 5 3 3 3 3 3 5 3 3 3 3 3 3 3 3 3 3 3
## [334] 3 3 3 3 5 2 5 3 3 3 3 3 5 3 3 5 5 5 3 3 3 5 5 5 3 3 5 5 5 3 5 5 2 3 3 3 3
## [371] 5 3 3 3 5 5 5 5 5 5 3 5 5 5 3 5 3 3 5 5 5 5 3 5 3 3 5 5 3 3 3 3 3 3 3 3 3
## [408] 5 3 3 5 3 3 5 3 5 5 3 3 5 5 3 3 3 3 3 3 3 3 3 3 3 3 5 3 3 3 3 5 3 3 3 3 3
## [445] 3cluster_size5 <- cbind(sum(groups_km5 == 1), sum(groups_km5 == 2),
sum(groups_km5 == 3), sum(groups_km5 == 4),sum(groups_km5 == 5))
cluster_size5## [,1] [,2] [,3] [,4] [,5]
## [1,] 1 6 288 1 149plot(datas, pch = groups_km5, col=groups_km5, lwd=2)
legend("topright", legend = 1:5, pch = 1:5, col=1:5, bty="n")
plot(silhouette(groups_km5, dists))
dc <- dist(datas, method = "euclidean")
dc## 1 2 3 4 5
## 2 2.774641e-01
## 3 2.629460e-01 4.699015e-02
## 4 3.121754e-01 3.567693e-01 3.105959e-01
## 5 2.580937e-01 1.020265e-01 5.505369e-02 2.574095e-01
## 6 6.900647e-01 5.140197e-01 5.608068e-01 8.701660e-01 6.154631e-01
## 7 2.213332e+00 2.337611e+00 2.366593e+00 2.523074e+00 2.402818e+00
## 8 6.992830e-01 5.094401e-01 5.557812e-01 8.662094e-01 6.098731e-01
## 9 2.647714e-01 8.114166e-02 3.462138e-02 2.793015e-01 2.189205e-02
## 10 2.980348e-01 2.742319e-02 4.533208e-02 3.527624e-01 9.535294e-02
## 11 2.693648e-01 6.936178e-02 2.402127e-02 2.919467e-01 3.453728e-02
## 12 2.493929e-01 1.869352e-01 1.402850e-01 1.707896e-01 8.661983e-02
## 13 7.397146e-01 5.302204e-01 5.752537e-01 8.852451e-01 6.278357e-01
## 14 3.757463e-01 1.780955e-01 2.250167e-01 5.315896e-01 2.800676e-01
## 15 2.802242e-01 4.684423e-02 1.728904e-02 3.176324e-01 6.022291e-02
## 16 8.245100e-01 9.626874e-01 9.870177e-01 1.135440e+00 1.019191e+00
## 17 3.234195e-01 4.841151e-02 8.733053e-02 3.962707e-01 1.388628e-01
## 18 8.568678e-01 6.591941e-01 7.047228e-01 1.015134e+00 7.578047e-01
## 19 2.375943e-01 1.840528e-01 1.379274e-01 1.727288e-01 8.588207e-02
## 20 2.557750e-01 1.110029e-01 6.401303e-02 2.481231e-01 9.286341e-03
## 21 2.704380e-01 6.682711e-02 2.199256e-02 2.947129e-01 3.730343e-02
## 22 8.869165e-01 1.106403e+00 1.115839e+00 1.164999e+00 1.131235e+00
## 23 3.445788e-01 4.305311e-01 3.851649e-01 7.939791e-02 3.332783e-01
## 24 2.729095e-01 1.380821e-02 5.782158e-02 3.651963e-01 1.126460e-01
## 25 1.506560e-01 1.272969e-01 1.144455e-01 2.994208e-01 1.246616e-01
## 26 2.681679e-01 2.686753e-01 2.223145e-01 8.843758e-02 1.689719e-01
## 27 2.765706e-01 5.367347e-02 1.562773e-02 3.094920e-01 5.208254e-02
## 28 2.525724e-01 1.263464e-01 7.939714e-02 2.323561e-01 2.505336e-02
## 29 3.517936e-01 8.839300e-02 1.312344e-01 4.408983e-01 1.835091e-01
## 30 4.397591e-01 1.974183e-01 2.415547e-01 5.512530e-01 2.938435e-01
## 31 4.973152e-01 3.097402e-01 3.566756e-01 6.652711e-01 4.115692e-01
## 32 2.050619e-01 1.049263e-01 6.803211e-02 2.601857e-01 5.461785e-02
## 33 4.060968e-01 1.562731e-01 2.000097e-01 5.096028e-01 2.521933e-01
## 34 2.513241e-01 2.047788e-01 1.582053e-01 1.527702e-01 1.046393e-01
## 35 3.343359e-01 6.252762e-02 1.029843e-01 4.119974e-01 1.545879e-01
## 36 3.332292e-01 6.103829e-02 1.013441e-01 4.103377e-01 1.529283e-01
## 37 2.495077e-01 2.585807e-01 2.128370e-01 9.876138e-02 1.608926e-01
## 38 2.682418e-01 2.688719e-01 2.225116e-01 8.824000e-02 1.691695e-01
## 39 2.155747e-01 1.493231e-01 1.052574e-01 2.093199e-01 6.113616e-02
## 40 3.693484e-01 1.093566e-01 1.522292e-01 4.616299e-01 2.042205e-01
## 41 4.049109e-01 1.547947e-01 1.985127e-01 5.081011e-01 2.506917e-01
## 42 2.828140e-01 4.246759e-02 2.029080e-02 3.231647e-01 6.575520e-02
## 43 2.620450e-01 8.900135e-02 4.219451e-02 2.710031e-01 1.359362e-02
## 44 3.023922e-01 2.768555e-02 5.270883e-02 3.605471e-01 1.031377e-01
## 45 5.335935e-01 3.061638e-01 3.508180e-01 6.606738e-01 4.032643e-01
## 46 4.114273e-01 1.628920e-01 2.067076e-01 5.163205e-01 2.589111e-01
## 47 3.228000e-01 3.914005e-01 3.457295e-01 3.915183e-02 2.933966e-01
## 48 2.585950e-01 1.002380e-01 5.327526e-02 2.592667e-01 1.857268e-03
## 49 2.500983e-01 1.438387e-01 9.697347e-02 2.144947e-01 4.291475e-02
## 50 3.109807e-01 3.585598e-01 3.124712e-01 3.656835e-03 2.594427e-01
## 51 3.638337e-01 1.021027e-01 1.447628e-01 4.541218e-01 1.967124e-01
## 52 5.783896e-01 3.566632e-01 4.014996e-01 7.114537e-01 4.540450e-01
## 53 2.777029e-01 5.147746e-02 1.572162e-02 3.120606e-01 5.465110e-02
## 54 2.648120e-01 8.103001e-02 3.451561e-02 2.794201e-01 2.201060e-02
## 55 6.257297e-01 5.042797e-01 5.505842e-01 8.480774e-01 6.052368e-01
## 56 2.634155e-01 2.601550e-01 2.138314e-01 9.683276e-02 1.606051e-01
## 57 2.587466e-01 2.451586e-01 1.987847e-01 1.119223e-01 1.455084e-01
## 58 3.357654e-01 3.935797e-01 3.474625e-01 3.690827e-02 2.943177e-01
## 59 5.547499e-01 3.298650e-01 3.745848e-01 6.844626e-01 4.270531e-01
## 60 2.840483e+00 3.058466e+00 3.070097e+00 3.103407e+00 3.086527e+00
## 61 4.078795e-01 1.584914e-01 2.022553e-01 5.118552e-01 2.544457e-01
## 62 3.336830e-01 8.090892e-02 1.267998e-01 4.373607e-01 1.810133e-01
## 63 3.648104e-01 1.047707e-01 1.478526e-01 4.574462e-01 2.000432e-01
## 64 2.697912e-01 2.729214e-01 2.265720e-01 8.416981e-02 1.732397e-01
## 65 2.529078e-01 1.244950e-01 7.753828e-02 2.342529e-01 2.315658e-02
## 66 2.452245e-01 1.660508e-01 1.194366e-01 1.914105e-01 6.612698e-02
## 67 3.829207e-01 1.269638e-01 1.702424e-01 4.797284e-01 2.223190e-01
## 68 2.529078e-01 1.244950e-01 7.753828e-02 2.342529e-01 2.315658e-02
## 69 3.107013e-01 3.325704e-02 6.643016e-02 3.747730e-01 1.173635e-01
## 70 3.410428e-01 7.158455e-02 1.127983e-01 4.219160e-01 1.645065e-01
## 71 3.818862e-01 1.850462e-01 2.319856e-01 5.387048e-01 2.870388e-01
## 72 1.928744e-01 2.147008e-01 1.726055e-01 1.561999e-01 1.291038e-01
## 73 3.556419e-01 9.122354e-02 1.334933e-01 4.427806e-01 1.853712e-01
## 74 2.585626e-01 2.392099e-01 1.927617e-01 1.180748e-01 1.393346e-01
## 75 6.230963e-01 4.050916e-01 4.499669e-01 7.598993e-01 5.024898e-01
## 76 2.492545e-01 1.849025e-01 1.382431e-01 1.728445e-01 8.456498e-02
## 77 2.790330e-01 2.947907e-01 2.484954e-01 6.219873e-02 1.952107e-01
## 78 3.836175e-01 1.284607e-01 1.718886e-01 4.814681e-01 2.240598e-01
## 79 2.916867e-01 2.121665e-02 4.193044e-02 3.512033e-01 9.396114e-02
## 80 2.799359e-01 3.111334e-01 2.651352e-01 4.593513e-02 2.124070e-01
## 81 2.593868e-01 9.750318e-02 5.056186e-02 2.621119e-01 4.702445e-03
## 82 2.971887e-01 2.763225e-02 4.388842e-02 3.512213e-01 9.381180e-02
## 83 2.163626e-01 1.239367e-01 8.087521e-02 2.350602e-01 4.464690e-02
## 84 4.603262e-01 2.278510e-01 2.728534e-01 5.831355e-01 3.258141e-01
## 85 3.652202e-01 1.039318e-01 1.466486e-01 4.560186e-01 1.986091e-01
## 86 6.047872e-01 8.318464e-01 8.384363e-01 8.848175e-01 8.513759e-01
## 87 3.468827e-01 7.946904e-02 1.211790e-01 4.303725e-01 1.729630e-01
## 88 1.624319e-01 1.329005e-01 1.051274e-01 2.595611e-01 9.649280e-02
## 89 5.869990e-01 3.743747e-01 4.199105e-01 7.303973e-01 4.731689e-01
## 90 7.845806e-01 1.038181e+00 1.037550e+00 1.024974e+00 1.041542e+00
## 91 2.487617e-01 1.710791e-01 1.243539e-01 1.868333e-01 7.057619e-02
## 92 3.959621e-01 1.435671e-01 1.871300e-01 4.966809e-01 2.392715e-01
## 93 3.337293e-01 3.905443e-01 3.444228e-01 3.386551e-02 2.912750e-01
## 94 3.050676e-01 2.886507e-02 5.717921e-02 3.652100e-01 1.078006e-01
## 95 2.492824e-01 1.853325e-01 1.386750e-01 1.724098e-01 8.499966e-02
## 96 2.492824e-01 1.533557e-01 1.065401e-01 2.048132e-01 5.259625e-02
## 97 3.391834e-01 6.907120e-02 1.100985e-01 4.191894e-01 1.617799e-01
## 98 2.697606e-01 6.841824e-02 2.325000e-02 2.929742e-01 3.556471e-02
## 99 2.576769e-01 1.035506e-01 5.657124e-02 2.558288e-01 1.580654e-03
## 100 3.928508e-01 1.930851e-01 2.400722e-01 5.476738e-01 2.951098e-01
## 101 8.383384e-01 9.284104e-01 9.593173e-01 1.149418e+00 9.985520e-01
## 102 3.551621e-01 9.058269e-02 1.328262e-01 4.421089e-01 1.846994e-01
## 103 3.129171e-01 3.548989e-02 7.000759e-02 3.784480e-01 1.210386e-01
## 104 3.175527e-01 4.073685e-02 7.738346e-02 3.859956e-01 1.285862e-01
## 105 2.518497e-01 2.082650e-01 1.617054e-01 1.492532e-01 1.081562e-01
## 106 2.650737e-01 1.128133e-01 1.515368e-01 4.369670e-01 2.021491e-01
## 107 2.535737e-01 1.210273e-01 7.405810e-02 2.378094e-01 1.960011e-02
## 108 3.388612e-01 6.863576e-02 1.096291e-01 4.187152e-01 1.613057e-01
## 109 6.772658e-01 4.683390e-01 5.136756e-01 8.239946e-01 5.666388e-01
## 110 4.983576e-01 2.661201e-01 3.106354e-01 6.204461e-01 3.630367e-01
## 111 3.625955e-01 1.004662e-01 1.430736e-01 4.524226e-01 1.950132e-01
## 112 2.523831e-01 2.115171e-01 1.649703e-01 1.459734e-01 1.114361e-01
## 113 2.509759e-01 1.365515e-01 8.964927e-02 2.219238e-01 3.548568e-02
## 114 3.271640e-01 5.449971e-02 9.513583e-02 4.044999e-01 1.471089e-01
## 115 3.484316e-01 9.130727e-02 1.358671e-01 4.462792e-01 1.891675e-01
## 116 2.869267e-01 2.801660e-02 3.110741e-02 3.393182e-01 8.200562e-02
## 117 4.718665e-01 2.354415e-01 2.798164e-01 5.895838e-01 3.321744e-01
## 118 4.028251e-01 1.521892e-01 1.958734e-01 5.054536e-01 2.480441e-01
## 119 4.383915e-01 1.957747e-01 2.398985e-01 5.495933e-01 2.921838e-01
## 120 2.640481e-01 2.571202e-01 2.107270e-01 1.000554e-01 1.573541e-01
## 121 2.548415e-01 1.150296e-01 6.804449e-02 2.439739e-01 1.343556e-02
## 122 3.525764e-01 8.712262e-02 1.292166e-01 4.384734e-01 1.810639e-01
## 123 7.194689e-01 5.087136e-01 5.537255e-01 8.637087e-01 6.062993e-01
## 124 8.106602e-01 6.202532e-01 6.662998e-01 9.768910e-01 7.200071e-01
## 125 5.445663e-01 3.184852e-01 3.631748e-01 6.730424e-01 4.156329e-01
## 126 2.636529e-01 2.559414e-01 2.095448e-01 1.012409e-01 1.561686e-01
## 127 2.838363e-01 2.342373e-02 3.129181e-02 3.409523e-01 8.392335e-02
## 128 8.251964e-01 6.202947e-01 6.654013e-01 9.754214e-01 7.180120e-01
## 129 1.141194e+00 9.527408e-01 9.983529e-01 1.308789e+00 1.051458e+00
## 130 2.652620e-01 7.980320e-02 3.335780e-02 2.807241e-01 2.331464e-02
## 131 2.079718e-01 1.366283e-01 9.429333e-02 2.242221e-01 5.710600e-02
## 132 3.586474e-01 9.522907e-02 1.376542e-01 4.469694e-01 1.895599e-01
## 133 2.115588e-01 3.176777e-01 2.763673e-01 1.036787e-01 2.320288e-01
## 134 2.491351e-01 1.557672e-01 1.089642e-01 2.023632e-01 5.504627e-02
## 135 3.040417e-01 3.430200e-01 2.968229e-01 1.379120e-02 2.436183e-01
## 136 5.850381e-01 3.634284e-01 4.082258e-01 7.181305e-01 4.607211e-01
## 137 2.932944e-01 2.968147e-02 3.721889e-02 3.439898e-01 8.658031e-02
## 138 2.540364e-01 2.203371e-01 1.738236e-01 1.370822e-01 1.203273e-01
## 139 2.757469e-01 2.873943e-01 2.410815e-01 6.962780e-02 1.877817e-01
## 140 1.067863e+00 1.230666e+00 1.251956e+00 1.372525e+00 1.280389e+00
## 141 3.883565e-01 1.402107e-01 1.847468e-01 4.949631e-01 2.376618e-01
## 142 3.426521e-01 7.980629e-02 1.233891e-01 4.335087e-01 1.762359e-01
## 143 4.296255e-01 1.855814e-01 2.296788e-01 5.393986e-01 2.819895e-01
## 144 2.440972e-01 1.597285e-01 1.131371e-01 1.976406e-01 6.002183e-02
## 145 3.730449e-01 1.297703e-01 1.753618e-01 4.859527e-01 2.291437e-01
## 146 4.990631e-01 3.331639e-01 3.800821e-01 6.852546e-01 4.351305e-01
## 147 2.638285e-01 5.723999e-02 1.062083e-02 3.012844e-01 4.486062e-02
## 148 2.458027e-01 1.904027e-01 1.439195e-01 1.668052e-01 9.073547e-02
## 149 4.760625e-01 2.779835e-01 3.248017e-01 6.342336e-01 3.795382e-01
## 150 2.445024e-01 4.789388e-02 2.016380e-02 3.106425e-01 6.240158e-02
## 151 2.353870e-01 2.124560e-01 1.667330e-01 1.445757e-01 1.152977e-01
## 152 6.341285e-01 4.170781e-01 4.619728e-01 7.719123e-01 5.145028e-01
## 153 2.425371e-01 3.842957e-02 3.322111e-02 3.257877e-01 7.995109e-02
## 154 2.580621e-01 1.021408e-01 5.516738e-02 2.572909e-01 1.185490e-04
## 155 4.311643e-01 1.870524e-01 2.311058e-01 5.407812e-01 2.833717e-01
## 156 1.116324e-01 2.451648e-01 2.504023e-01 3.999930e-01 2.689860e-01
## 157 2.567917e-01 2.324587e-01 1.859880e-01 1.248716e-01 1.325378e-01
## 158 2.495139e-01 1.885382e-01 1.418952e-01 1.691695e-01 8.824000e-02
## 159 2.538300e-01 1.197572e-01 7.278389e-02 2.391134e-01 1.829607e-02
## 160 2.602538e-01 9.462345e-02 4.771437e-02 2.651152e-01 7.705687e-03
## 161 2.871506e-01 3.117533e-01 2.654955e-01 4.516718e-02 2.122423e-01
## 162 3.250287e-01 3.773004e-01 3.311595e-01 2.058802e-02 2.779975e-01
## 163 3.722790e-01 1.131877e-01 1.561606e-01 4.655816e-01 2.081721e-01
## 164 3.733975e-01 1.146457e-01 1.576547e-01 4.670832e-01 2.096737e-01
## 165 3.583060e-01 9.477482e-02 1.371831e-01 4.464952e-01 1.890857e-01
## 166 3.108671e-01 3.341624e-02 6.669906e-02 3.750496e-01 1.176402e-01
## 167 1.560642e-01 3.444022e-01 3.505718e-01 4.679477e-01 3.673349e-01
## 168 3.235675e-01 9.200039e-02 1.389892e-01 4.475419e-01 1.940242e-01
## 169 2.552080e-01 9.141843e-02 4.443774e-02 2.669177e-01 1.110263e-02
## 170 5.874713e-01 3.661080e-01 4.109110e-01 7.208176e-01 4.634082e-01
## 171 1.221786e-01 2.846471e-01 2.518576e-01 1.913038e-01 2.218797e-01
## 172 2.720414e-01 3.943971e-02 1.103085e-02 3.201771e-01 6.347643e-02
## 173 4.477811e-01 2.192528e-01 2.648051e-01 5.753565e-01 3.182976e-01
## 174 2.294807e-01 4.825589e-02 5.656949e-02 3.375200e-01 1.001206e-01
## 175 1.936953e-01 2.454296e-01 2.035565e-01 1.338076e-01 1.595368e-01
## 176 1.874249e-01 1.112715e-01 8.022767e-02 2.647439e-01 7.331997e-02
## 177 1.899088e-01 1.274536e-01 1.456974e-01 3.859521e-01 1.821612e-01
## 178 2.635744e-01 2.557056e-01 2.093083e-01 1.014780e-01 1.559315e-01
## 179 2.374984e-01 2.417936e-01 1.963884e-01 1.163211e-01 1.453232e-01
## 180 6.961252e-01 4.838165e-01 5.288011e-01 8.387739e-01 5.813644e-01
## 181 2.487565e-01 1.700648e-01 1.233346e-01 1.878607e-01 6.954877e-02
## 182 3.286426e-01 5.490364e-02 9.447828e-02 4.033828e-01 1.459734e-01
## 183 3.713543e-01 1.201241e-01 1.647386e-01 4.750652e-01 2.178422e-01
## 184 4.675542e-01 3.525876e-01 3.976311e-01 6.889135e-01 4.513586e-01
## 185 4.677415e-01 2.317698e-01 2.762643e-01 5.861504e-01 3.287444e-01
## 186 4.585299e-01 2.360102e-01 2.818935e-01 5.924892e-01 3.356719e-01
## 187 2.390013e-01 9.964196e-02 5.396617e-02 2.571274e-01 1.959069e-02
## 188 1.367131e-01 3.138843e-01 2.804374e-01 1.869219e-01 2.486649e-01
## 189 2.998545e-01 3.526187e-01 3.068165e-01 1.337893e-02 2.543404e-01
## 190 1.541058e+00 1.726661e+00 1.744670e+00 1.833435e+00 1.768954e+00
## 191 3.609613e-01 1.026994e-01 1.464063e-01 4.563831e-01 1.990362e-01
## 192 2.680058e-01 2.682429e-01 2.218809e-01 8.887226e-02 1.685372e-01
## 193 3.324154e-01 5.994476e-02 1.001339e-01 4.091127e-01 1.517032e-01
## 194 2.463715e-01 2.547955e-01 2.091398e-01 1.027539e-01 1.574124e-01
## 195 2.871651e-01 3.934965e-01 3.498628e-01 7.781979e-02 3.010060e-01
## 196 3.727706e-01 4.956655e-01 4.515617e-01 1.545799e-01 4.015923e-01
## 197 7.322853e-02 2.852380e-01 2.827146e-01 3.827456e-01 2.915739e-01
## 198 2.499628e-01 1.935836e-01 1.469630e-01 1.640719e-01 9.333760e-02
## 199 2.552337e-01 1.133028e-01 6.631494e-02 2.457521e-01 1.165732e-02
## 200 4.662383e-01 2.288487e-01 2.731882e-01 5.829451e-01 3.255356e-01
## 201 2.792122e-01 4.866082e-02 1.645990e-02 3.154195e-01 5.800999e-02
## 202 2.610968e-01 8.694992e-02 4.008512e-02 2.726672e-01 1.533259e-02
## 203 2.088582e-01 1.705485e-01 1.269050e-01 1.898909e-01 8.211697e-02
## 204 6.633063e-02 3.272678e-01 3.057192e-01 2.849920e-01 2.902613e-01
## 205 1.029361e-01 3.149545e-01 3.151695e-01 4.149169e-01 3.261666e-01
## 206 4.352824e-01 5.261100e-01 4.801672e-01 1.697707e-01 4.271750e-01
## 207 2.600269e-01 3.358043e-01 2.915564e-01 5.430826e-02 2.419688e-01
## 208 2.848692e-01 3.929098e-02 2.325000e-02 3.274324e-01 7.002296e-02
## 209 2.792122e-01 4.866082e-02 1.645990e-02 3.154195e-01 5.800999e-02
## 210 1.843913e-01 3.260743e-01 2.877680e-01 1.391519e-01 2.482282e-01
## 211 4.118871e-01 1.856892e-01 2.318989e-01 5.424031e-01 2.860639e-01
## 212 3.129171e-01 3.548989e-02 7.000759e-02 3.784480e-01 1.210386e-01
## 213 2.651715e-01 6.853631e-02 1.087862e-01 4.042129e-01 1.612026e-01
## 214 2.656483e-01 2.617573e-01 2.153774e-01 9.539245e-02 1.620170e-01
## 215 2.874213e-01 2.081347e-02 3.698688e-02 3.466254e-01 8.952304e-02
## 216 6.815329e-01 4.681937e-01 5.131597e-01 8.231254e-01 5.657160e-01
## 217 3.547111e-01 8.997994e-02 1.321983e-01 4.414766e-01 1.840671e-01
## 218 3.177047e-01 4.136507e-01 3.690220e-01 7.467322e-02 3.184261e-01
## 219 2.488044e-01 1.742007e-01 1.274908e-01 1.836720e-01 7.373750e-02
## 220 5.354171e-01 6.949876e-01 7.140636e-01 8.457245e-01 7.413438e-01
## 221 4.691251e-01 2.839633e-01 3.309506e-01 6.386502e-01 3.859522e-01
## 222 2.179675e-01 1.951649e-01 1.505300e-01 1.639068e-01 1.021159e-01
## 223 2.511306e-01 2.034081e-01 1.568290e-01 1.541533e-01 1.032562e-01
## 224 2.905852e-01 3.208266e-02 3.259206e-02 3.388131e-01 8.140367e-02
## 225 3.428163e-01 5.360045e-01 5.471262e-01 6.505297e-01 5.667500e-01
## 226 2.496974e-01 2.345995e-01 1.884439e-01 1.221789e-01 1.357454e-01
## 6 7 8 9 10
## 2
## 3
## 4
## 5
## 6
## 7 2.110196e+00
## 8 3.952216e-02 2.148965e+00
## 9 5.939089e-01 2.393589e+00 5.881155e-01
## 10 5.217875e-01 2.363840e+00 5.151893e-01 7.346088e-02
## 11 5.814704e-01 2.388334e+00 5.755526e-01 1.264523e-02 6.081565e-02
## 12 7.009514e-01 2.440917e+00 6.960434e-01 1.085119e-01 1.819728e-01
## 13 1.079808e-01 2.210091e+00 6.971212e-02 6.059436e-01 5.324827e-01
## 14 3.393049e-01 2.224538e+00 3.387753e-01 2.592101e-01 1.909215e-01
## 15 5.562332e-01 2.377830e+00 5.500459e-01 3.833085e-02 3.513003e-02
## 16 8.841373e-01 1.389357e+00 9.221228e-01 1.011713e+00 9.897499e-01
## 17 4.790876e-01 2.346379e+00 4.719640e-01 1.169712e-01 4.351499e-02
## 18 1.729244e-01 2.168971e+00 1.576149e-01 7.359221e-01 6.624972e-01
## 19 6.977512e-01 2.429779e+00 6.934888e-01 1.076108e-01 1.808118e-01
## 20 6.246132e-01 2.406782e+00 6.191052e-01 3.117840e-02 1.046393e-01
## 21 5.787506e-01 2.387191e+00 5.728050e-01 1.541137e-02 5.804951e-02
## 22 1.180081e+00 1.445434e+00 1.214555e+00 1.131023e+00 1.133406e+00
## 23 9.418488e-01 2.539262e+00 9.393119e-01 3.551047e-01 4.283944e-01
## 24 5.050415e-01 2.323977e+00 5.013008e-01 9.241284e-02 4.028037e-02
## 25 5.913174e-01 2.284683e+00 5.937908e-01 1.239028e-01 1.473899e-01
## 26 7.824586e-01 2.479403e+00 7.780606e-01 1.908639e-01 2.643248e-01
## 27 5.642271e-01 2.381134e+00 5.581278e-01 3.019049e-02 4.327040e-02
## 28 6.401579e-01 2.413580e+00 6.347838e-01 4.694542e-02 1.204063e-01
## 29 4.350113e-01 2.327380e+00 4.274126e-01 1.616217e-01 8.819360e-02
## 30 3.298858e-01 2.293317e+00 3.193715e-01 2.719515e-01 1.984906e-01
## 31 2.050782e-01 2.176425e+00 2.054941e-01 3.902166e-01 3.191006e-01
## 32 6.114563e-01 2.354881e+00 6.093764e-01 5.994886e-02 1.124635e-01
## 33 3.695769e-01 2.306878e+00 3.602184e-01 2.303013e-01 1.568404e-01
## 34 7.187695e-01 2.449153e+00 7.139830e-01 1.265313e-01 1.999922e-01
## 35 4.639388e-01 2.341255e+00 4.565103e-01 1.326959e-01 5.923500e-02
## 36 4.655548e-01 2.341870e+00 4.581525e-01 1.310362e-01 5.757531e-02
## 37 7.715238e-01 2.460616e+00 7.679148e-01 1.826826e-01 2.559285e-01
## 38 7.826543e-01 2.479498e+00 7.782575e-01 1.910615e-01 2.645224e-01
## 39 6.610765e-01 2.394504e+00 6.579136e-01 8.027231e-02 1.500954e-01
## 40 4.157684e-01 2.323325e+00 4.074676e-01 1.823284e-01 1.088675e-01
## 41 3.710159e-01 2.307380e+00 3.616945e-01 2.287996e-01 1.553387e-01
## 42 5.508030e-01 2.375597e+00 5.445543e-01 4.386314e-02 2.959774e-02
## 43 6.020764e-01 2.397068e+00 5.963618e-01 8.298432e-03 8.175932e-02
## 44 5.141669e-01 2.360799e+00 5.074703e-01 8.124560e-02 7.784720e-03
## 45 2.289525e-01 2.260960e+00 2.135449e-01 3.813722e-01 3.079114e-01
## 46 3.631454e-01 2.304645e+00 3.536175e-01 2.370190e-01 1.635581e-01
## 47 9.036625e-01 2.527204e+00 9.005742e-01 3.152565e-01 3.886362e-01
## 48 6.136336e-01 2.402029e+00 6.080268e-01 2.003479e-02 9.349567e-02
## 49 6.577803e-01 2.421381e+00 6.525502e-01 6.480680e-02 1.382677e-01
## 50 8.718014e-01 2.521468e+00 8.679912e-01 2.813334e-01 3.547909e-01
## 51 4.230337e-01 2.325979e+00 4.148775e-01 1.748203e-01 1.013594e-01
## 52 1.846035e-01 2.246217e+00 1.654609e-01 4.321531e-01 3.586927e-01
## 53 5.617043e-01 2.380089e+00 5.555775e-01 3.275905e-02 4.070183e-02
## 54 5.937923e-01 2.393540e+00 5.879977e-01 1.185490e-04 7.334233e-02
## 55 1.403828e-01 1.992527e+00 1.779043e-01 5.851588e-01 5.188584e-01
## 56 7.739079e-01 2.473763e+00 7.695567e-01 1.824959e-01 2.559541e-01
## 57 7.589815e-01 2.466771e+00 7.545338e-01 1.673993e-01 2.408577e-01
## 58 9.068115e-01 2.541988e+00 9.030139e-01 3.162098e-01 3.896707e-01
## 59 2.081471e-01 2.254566e+00 1.910740e-01 4.051611e-01 3.317002e-01
## 60 3.026949e+00 1.314517e+00 3.065856e+00 3.086078e+00 3.085706e+00
## 61 3.674193e-01 2.306128e+00 3.580047e-01 2.325537e-01 1.590928e-01
## 62 4.345760e-01 2.308478e+00 4.289956e-01 1.593696e-01 8.764840e-02
## 63 4.192854e-01 2.322798e+00 4.112613e-01 1.781526e-01 1.047007e-01
## 64 7.866873e-01 2.481456e+00 7.823130e-01 1.951317e-01 2.685926e-01
## 65 6.382873e-01 2.412758e+00 6.328974e-01 4.504863e-02 1.185095e-01
## 66 6.800641e-01 2.428465e+00 6.752130e-01 8.799536e-02 1.614237e-01
## 67 3.982925e-01 2.317017e+00 3.896213e-01 2.004269e-01 1.269660e-01
## 68 6.382873e-01 2.412758e+00 6.328974e-01 4.504863e-02 1.185095e-01
## 69 5.002541e-01 2.355299e+00 4.933698e-01 9.547149e-02 2.201060e-02
## 70 4.542872e-01 2.337599e+00 4.466992e-01 1.426145e-01 6.915360e-02
## 71 3.321700e-01 2.221606e+00 3.316969e-01 2.661426e-01 1.976056e-01
## 72 7.213699e-01 2.399267e+00 7.199664e-01 1.487441e-01 2.178097e-01
## 73 4.340236e-01 2.330026e+00 4.260768e-01 1.634791e-01 9.001823e-02
## 74 7.531042e-01 2.465305e+00 7.485354e-01 1.612267e-01 2.346876e-01
## 75 1.482310e-01 2.235846e+00 1.231359e-01 4.805978e-01 4.071369e-01
## 76 6.989202e-01 2.439985e+00 6.939979e-01 1.064570e-01 1.799179e-01
## 77 8.084642e-01 2.492113e+00 8.042072e-01 2.171028e-01 2.905637e-01
## 78 3.963591e-01 2.315508e+00 3.877436e-01 2.021679e-01 1.287084e-01
## 79 5.220899e-01 2.358455e+00 5.159971e-01 7.213842e-02 6.744499e-03
## 80 8.243217e-01 2.493204e+00 8.205491e-01 2.342837e-01 3.077089e-01
## 81 6.108312e-01 2.400822e+00 6.051987e-01 1.718961e-02 9.065049e-02
## 82 5.232967e-01 2.364444e+00 5.167177e-01 7.191975e-02 1.541137e-03
## 83 6.353073e-01 2.380545e+00 6.321979e-01 5.981804e-02 1.260993e-01
## 84 2.961383e-01 2.272577e+00 2.859629e-01 3.039364e-01 2.305436e-01
## 85 4.211974e-01 2.325306e+00 4.130052e-01 1.767171e-01 1.032562e-01
## 86 9.709828e-01 1.681859e+00 1.001619e+00 8.520666e-01 8.584696e-01
## 87 4.460676e-01 2.334510e+00 4.383381e-01 1.510710e-01 7.761010e-02
## 88 6.223153e-01 2.324106e+00 6.228548e-01 1.024079e-01 1.464242e-01
## 89 1.577251e-01 2.221596e+00 1.407394e-01 4.513018e-01 3.779457e-01
## 90 1.218117e+00 1.675585e+00 1.248124e+00 1.045866e+00 1.063546e+00
## 91 6.850959e-01 2.433673e+00 6.800744e-01 9.246824e-02 1.659291e-01
## 92 3.819757e-01 2.311222e+00 3.729272e-01 2.173794e-01 1.439185e-01
## 93 9.037895e-01 2.540414e+00 8.999793e-01 3.131670e-01 3.866279e-01
## 94 5.096047e-01 2.358988e+00 5.028477e-01 8.590853e-02 1.244765e-02
## 95 6.993499e-01 2.440182e+00 6.944306e-01 1.068917e-01 1.803526e-01
## 96 6.673375e-01 2.425655e+00 6.621824e-01 7.448831e-02 1.479492e-01
## 97 4.569393e-01 2.338600e+00 4.493958e-01 1.398879e-01 6.642697e-02
## 98 5.804601e-01 2.387909e+00 5.745321e-01 1.367265e-02 5.978823e-02
## 99 6.170203e-01 2.403491e+00 6.114444e-01 2.347271e-02 9.693359e-02
## 100 3.227894e-01 2.222971e+00 3.217000e-01 2.740462e-01 2.046401e-01
## 101 7.654190e-01 1.410567e+00 8.045768e-01 9.877552e-01 9.543071e-01
## 102 4.346752e-01 2.330268e+00 4.267404e-01 1.628073e-01 8.934645e-02
## 103 4.966629e-01 2.353890e+00 4.897284e-01 9.914651e-02 2.568562e-02
## 104 4.892912e-01 2.351012e+00 4.822513e-01 1.066941e-01 3.323325e-02
## 105 7.222484e-01 2.450773e+00 7.174848e-01 1.300483e-01 2.035092e-01
## 106 4.437133e-01 2.227214e+00 4.466723e-01 1.849734e-01 1.375068e-01
## 107 6.347803e-01 2.411219e+00 6.293606e-01 4.149216e-02 1.149530e-01
## 108 4.574006e-01 2.338775e+00 4.498648e-01 1.394137e-01 6.595278e-02
## 109 1.001140e-01 2.208190e+00 6.573850e-02 5.447537e-01 4.713207e-01
## 110 2.652786e-01 2.272297e+00 2.520947e-01 3.411446e-01 2.676837e-01
## 111 4.246791e-01 2.326582e+00 4.165549e-01 1.731211e-01 9.966022e-02
## 112 7.254930e-01 2.452287e+00 7.207507e-01 1.333281e-01 2.067890e-01
## 113 6.504490e-01 2.418123e+00 6.451600e-01 5.737773e-02 1.308386e-01
## 114 4.706042e-01 2.341334e+00 4.635314e-01 1.252219e-01 5.180946e-02
## 115 4.276273e-01 2.315812e+00 4.208734e-01 1.673430e-01 9.433804e-02
## 116 5.341034e-01 2.364955e+00 5.280009e-01 6.016007e-02 1.423075e-02
## 117 2.938375e-01 2.281437e+00 2.819877e-01 3.102823e-01 2.368214e-01
## 118 3.735543e-01 2.308266e+00 3.642976e-01 2.261520e-01 1.526912e-01
## 119 3.314582e-01 2.293844e+00 3.209952e-01 2.702918e-01 1.968309e-01
## 120 7.709491e-01 2.473844e+00 7.664857e-01 1.792461e-01 2.527070e-01
## 121 6.287029e-01 2.408563e+00 6.232307e-01 3.532761e-02 1.087885e-01
## 122 4.382022e-01 2.331576e+00 4.303322e-01 1.591718e-01 8.571095e-02
## 123 1.058114e-01 2.214032e+00 6.628922e-02 5.844072e-01 5.109463e-01
## 124 1.233274e-01 2.142770e+00 1.124745e-01 6.981776e-01 6.249586e-01
## 125 2.180589e-01 2.257607e+00 2.018238e-01 3.937408e-01 3.202800e-01
## 126 7.697748e-01 2.473279e+00 7.653047e-01 1.780606e-01 2.515215e-01
## 127 5.317331e-01 2.360111e+00 5.259497e-01 6.220903e-02 1.506046e-02
## 128 1.538693e-01 2.195804e+00 1.299339e-01 6.961199e-01 6.226590e-01
## 129 4.513247e-01 2.145774e+00 4.463485e-01 1.029575e+00 9.561455e-01
## 130 5.925092e-01 2.392995e+00 5.867020e-01 1.422588e-03 7.203829e-02
## 131 6.467226e-01 2.380218e+00 6.440573e-01 7.332881e-02 1.395791e-01
## 132 4.299625e-01 2.328526e+00 4.219396e-01 1.676678e-01 9.420696e-02
## 133 8.187937e-01 2.419765e+00 8.191089e-01 2.522229e-01 3.216140e-01
## 134 6.697566e-01 2.426741e+00 6.646201e-01 7.693832e-02 1.503992e-01
## 135 8.564787e-01 2.516109e+00 8.524593e-01 2.655103e-01 3.389712e-01
## 136 1.799696e-01 2.245918e+00 1.599243e-01 4.388290e-01 3.653681e-01
## 137 5.303808e-01 2.367292e+00 5.238902e-01 6.468825e-02 8.772628e-03
## 138 7.342902e-01 2.456409e+00 7.296047e-01 1.422193e-01 2.156802e-01
## 139 8.010996e-01 2.488493e+00 7.968036e-01 2.096737e-01 2.831346e-01
## 140 1.156571e+00 1.159320e+00 1.195104e+00 1.274646e+00 1.257970e+00
## 141 3.811004e-01 2.302486e+00 3.730853e-01 2.157909e-01 1.424483e-01
## 142 4.410493e-01 2.325018e+00 4.340510e-01 1.543764e-01 8.115370e-02
## 143 3.409162e-01 2.296437e+00 3.308360e-01 2.600975e-01 1.866370e-01
## 144 6.737387e-01 2.424549e+00 6.689175e-01 8.186200e-02 1.552556e-01
## 145 3.872966e-01 2.293681e+00 3.807454e-01 2.073715e-01 1.345969e-01
## 146 1.920465e-01 2.133825e+00 2.006126e-01 4.142701e-01 3.452059e-01
## 147 5.706748e-01 2.375336e+00 5.653522e-01 2.404474e-02 5.262930e-02
## 148 7.043576e-01 2.439256e+00 6.996950e-01 1.126110e-01 1.860449e-01
## 149 2.360426e-01 2.201527e+00 2.334707e-01 3.580561e-01 2.864250e-01
## 150 5.595343e-01 2.348940e+00 5.559277e-01 4.618036e-02 5.680688e-02
## 151 7.255904e-01 2.437733e+00 7.218203e-01 1.369707e-01 2.100287e-01
## 152 1.400808e-01 2.233086e+00 1.131972e-01 4.926107e-01 4.191499e-01
## 153 5.444963e-01 2.333405e+00 5.415778e-01 6.343146e-02 5.549870e-02
## 154 6.155799e-01 2.402868e+00 6.099909e-01 2.201060e-02 9.547149e-02
## 155 3.398209e-01 2.296663e+00 3.296224e-01 2.614796e-01 1.880188e-01
## 156 5.869805e-01 2.145954e+00 5.989212e-01 2.664851e-01 2.711555e-01
## 157 7.463754e-01 2.462111e+00 7.417655e-01 1.544299e-01 2.278908e-01
## 158 7.025531e-01 2.441653e+00 6.976562e-01 1.101321e-01 1.835929e-01
## 159 6.334946e-01 2.410656e+00 6.280639e-01 4.018812e-02 1.136490e-01
## 160 6.078736e-01 2.399551e+00 6.022136e-01 1.418637e-02 8.764725e-02
## 161 8.253522e-01 2.500475e+00 8.211820e-01 2.341343e-01 3.075952e-01
## 162 8.906047e-01 2.533576e+00 8.867385e-01 2.998895e-01 3.733504e-01
## 163 4.119482e-01 2.321938e+00 4.035691e-01 1.862800e-01 1.128192e-01
## 164 4.104971e-01 2.321412e+00 4.020880e-01 1.877817e-01 1.143208e-01
## 165 4.304221e-01 2.328695e+00 4.224079e-01 1.671937e-01 9.373277e-02
## 166 4.999838e-01 2.355193e+00 4.930957e-01 9.574810e-02 2.228722e-02
## 167 6.280588e-01 2.060896e+00 6.453820e-01 3.659262e-01 3.707299e-01
## 168 4.226530e-01 2.281913e+00 4.193138e-01 1.729943e-01 1.050333e-01
## 169 6.051699e-01 2.393526e+00 5.998692e-01 1.374829e-02 8.610660e-02
## 170 1.778030e-01 2.245248e+00 1.574828e-01 4.415161e-01 3.680552e-01
## 171 7.615069e-01 2.331971e+00 7.653197e-01 2.375280e-01 2.958841e-01
## 172 5.519879e-01 2.367225e+00 5.465159e-01 4.204642e-02 3.441536e-02
## 173 3.006113e-01 2.264685e+00 2.920739e-01 2.964635e-01 2.232797e-01
## 174 5.345043e-01 2.310110e+00 5.331587e-01 8.545500e-02 7.193558e-02
## 175 7.505200e-01 2.405743e+00 7.496342e-01 1.794669e-01 2.487665e-01
## 176 6.101715e-01 2.338038e+00 6.093028e-01 7.737295e-02 1.226407e-01
## 177 5.124537e-01 2.222003e+00 5.176820e-01 1.716120e-01 1.547006e-01
## 178 7.695400e-01 2.473166e+00 7.650685e-01 1.778235e-01 2.512844e-01
## 179 7.542710e-01 2.446738e+00 7.509360e-01 1.669691e-01 2.399306e-01
## 180 1.087096e-01 2.218849e+00 7.080985e-02 5.594724e-01 4.860115e-01
## 181 6.840808e-01 2.433212e+00 6.790518e-01 9.144082e-02 1.649017e-01
## 182 4.723304e-01 2.344460e+00 4.650353e-01 1.240813e-01 5.062044e-02
## 183 3.999021e-01 2.307208e+00 3.925008e-01 1.959886e-01 1.227569e-01
## 184 2.351579e-01 2.057810e+00 2.557120e-01 4.322056e-01 3.701617e-01
## 185 2.962418e-01 2.280303e+00 2.848086e-01 3.068529e-01 2.333947e-01
## 186 2.822982e-01 2.251992e+00 2.743322e-01 3.138750e-01 2.408594e-01
## 187 6.134202e-01 2.385567e+00 6.090821e-01 3.013374e-02 9.834589e-02
## 188 7.899034e-01 2.337380e+00 7.940816e-01 2.650208e-01 3.247057e-01
## 189 8.653086e-01 2.510200e+00 8.619234e-01 2.762064e-01 3.496036e-01
## 190 1.657969e+00 8.238653e-01 1.696915e+00 1.765094e+00 1.754078e+00
## 191 4.192702e-01 2.318981e+00 4.116780e-01 1.771579e-01 1.037853e-01
## 192 7.820279e-01 2.479195e+00 7.776275e-01 1.904293e-01 2.638901e-01
## 193 4.667479e-01 2.342325e+00 4.593646e-01 1.298112e-01 5.635031e-02
## 194 7.676127e-01 2.457143e+00 7.640851e-01 1.791718e-01 2.523554e-01
## 195 8.999774e-01 2.482281e+00 8.991992e-01 3.223503e-01 3.944124e-01
## 196 1.002521e+00 2.538039e+00 1.001823e+00 4.231723e-01 4.957861e-01
## 197 6.429607e-01 2.147095e+00 6.554262e-01 2.930891e-01 3.096425e-01
## 198 7.075930e-01 2.443975e+00 7.027309e-01 1.152297e-01 1.886905e-01
## 199 6.269501e-01 2.407799e+00 6.214626e-01 3.354938e-02 1.070103e-01
## 200 3.000404e-01 2.283453e+00 2.884446e-01 3.036436e-01 2.301827e-01
## 201 5.584059e-01 2.378725e+00 5.522427e-01 3.611794e-02 3.734294e-02
## 202 6.001702e-01 2.394957e+00 5.945409e-01 6.818921e-03 8.011476e-02
## 203 6.812551e-01 2.398610e+00 6.785341e-01 1.018061e-01 1.718160e-01
## 204 7.561946e-01 2.239276e+00 7.650476e-01 3.010381e-01 3.449803e-01
## 205 6.459919e-01 2.112641e+00 6.604826e-01 3.269639e-01 3.400848e-01
## 206 1.038702e+00 2.611843e+00 1.035448e+00 4.490669e-01 5.225274e-01
## 207 8.448341e-01 2.469314e+00 8.431161e-01 2.634236e-01 3.358299e-01
## 208 5.466153e-01 2.373883e+00 5.403186e-01 4.813091e-02 2.532998e-02
## 209 5.584059e-01 2.378725e+00 5.522427e-01 3.611794e-02 3.734294e-02
## 210 8.174709e-01 2.386573e+00 8.196069e-01 2.670680e-01 3.330262e-01
## 211 3.299906e-01 2.262588e+00 3.238852e-01 2.643588e-01 1.918364e-01
## 212 4.966629e-01 2.353890e+00 4.897284e-01 9.914651e-02 2.568562e-02
## 213 4.686657e-01 2.270695e+00 4.683695e-01 1.428813e-01 9.340809e-02
## 214 7.755681e-01 2.476070e+00 7.711313e-01 1.839091e-01 2.573699e-01
## 215 5.262472e-01 2.358396e+00 5.203585e-01 6.776477e-02 1.062451e-02
## 216 1.133272e-01 2.222009e+00 7.770493e-02 5.438239e-01 4.703630e-01
## 217 4.352884e-01 2.330495e+00 4.273650e-01 1.621751e-01 8.871419e-02
## 218 9.229545e-01 2.512119e+00 9.212732e-01 3.400866e-01 4.129488e-01
## 219 6.882195e-01 2.435094e+00 6.832207e-01 9.562955e-02 1.690904e-01
## 220 7.367427e-01 1.677921e+00 7.697610e-01 7.359458e-01 7.224001e-01
## 221 2.323580e-01 2.178737e+00 2.337412e-01 3.647649e-01 2.944237e-01
## 222 7.068772e-01 2.416611e+00 7.038424e-01 1.230616e-01 1.948731e-01
## 223 7.174016e-01 2.448517e+00 7.126059e-01 1.251483e-01 1.986091e-01
## 224 5.354544e-01 2.369342e+00 5.290257e-01 5.951161e-02 1.394927e-02
## 225 7.048564e-01 1.872558e+00 7.310538e-01 5.644879e-01 5.630848e-01
## 226 7.482043e-01 2.456326e+00 7.440377e-01 1.576036e-01 2.309977e-01
## 11 12 13 14 15
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12 1.211571e-01
## 13 5.932984e-01 7.144555e-01
## 14 2.472440e-01 3.637879e-01 3.691805e-01
## 15 2.568562e-02 1.468427e-01 5.676128e-01 2.231686e-01
## 16 1.007585e+00 1.052731e+00 9.917781e-01 8.770966e-01 9.996399e-01
## 17 1.043263e-01 2.254817e-01 4.889759e-01 1.523263e-01 7.864167e-02
## 18 7.232825e-01 8.443921e-01 1.314863e-01 4.933053e-01 6.976091e-01
## 19 1.201887e-01 1.182041e-02 7.130107e-01 3.598200e-01 1.457735e-01
## 20 4.382363e-02 7.733348e-02 6.371220e-01 2.889613e-01 6.950925e-02
## 21 2.766144e-03 1.239233e-01 5.905322e-01 2.446356e-01 2.291948e-02
## 22 1.131094e+00 1.136216e+00 1.283114e+00 1.077620e+00 1.131672e+00
## 23 3.677156e-01 2.470319e-01 9.604184e-01 6.025921e-01 3.933382e-01
## 24 8.111927e-02 1.962260e-01 5.235785e-01 1.677197e-01 5.986693e-02
## 25 1.252187e-01 1.602685e-01 6.249520e-01 2.560368e-01 1.316439e-01
## 26 2.035092e-01 8.235206e-02 7.968076e-01 4.444151e-01 2.291948e-01
## 27 1.754526e-02 1.387024e-01 5.757531e-01 2.307611e-01 8.140367e-03
## 28 5.959065e-02 6.156646e-02 6.528890e-01 3.041154e-01 8.527627e-02
## 29 1.489798e-01 2.701178e-01 4.443756e-01 1.150884e-01 1.233031e-01
## 30 2.593062e-01 3.804634e-01 3.339921e-01 8.587619e-02 2.336206e-01
## 31 3.779111e-01 4.965155e-01 2.425631e-01 1.342793e-01 3.529895e-01
## 32 6.620711e-02 9.982897e-02 6.331918e-01 2.722184e-01 8.349632e-02
## 33 2.176560e-01 3.388131e-01 3.756424e-01 8.332769e-02 1.919704e-01
## 34 1.391766e-01 1.801945e-02 7.324749e-01 3.813670e-01 1.648622e-01
## 35 1.200507e-01 2.412078e-01 4.732477e-01 1.397321e-01 9.436503e-02
## 36 1.183910e-01 2.395481e-01 4.749074e-01 1.410806e-01 9.270534e-02
## 37 1.952793e-01 7.525906e-02 7.880502e-01 4.328394e-01 2.208835e-01
## 38 2.037068e-01 8.254964e-02 7.970051e-01 4.446093e-01 2.293924e-01
## 39 9.188807e-02 4.929587e-02 6.795407e-01 3.222813e-01 1.161465e-01
## 40 1.696832e-01 2.908403e-01 4.236152e-01 1.036644e-01 1.439976e-01
## 41 2.161544e-01 3.373115e-01 3.771440e-01 8.362269e-02 1.904688e-01
## 42 3.121791e-02 1.523750e-01 5.620805e-01 2.180312e-01 5.532288e-03
## 43 2.094366e-02 1.002134e-01 6.142420e-01 2.670969e-01 4.662929e-02
## 44 6.860037e-02 1.897575e-01 5.246980e-01 1.839187e-01 4.291475e-02
## 45 3.687270e-01 4.898841e-01 2.245714e-01 1.582336e-01 3.430414e-01
## 46 2.243738e-01 3.455309e-01 3.689246e-01 8.233096e-02 1.986882e-01
## 47 3.278852e-01 2.069701e-01 9.209174e-01 5.645758e-01 3.535408e-01
## 48 3.268002e-02 8.847709e-02 6.259784e-01 2.782919e-01 5.836564e-02
## 49 7.745203e-02 4.370508e-02 6.707504e-01 3.213538e-01 1.031377e-01
## 50 2.939779e-01 1.728319e-01 8.872657e-01 5.331215e-01 3.196623e-01
## 51 1.621751e-01 2.833322e-01 4.311233e-01 1.084344e-01 1.364895e-01
## 52 4.195079e-01 5.406645e-01 1.737987e-01 2.028254e-01 3.938225e-01
## 53 2.011382e-02 1.412709e-01 5.731846e-01 2.283613e-01 5.571804e-03
## 54 1.252668e-02 1.086304e-01 6.058251e-01 2.590977e-01 3.821230e-02
## 55 5.736218e-01 6.857687e-01 2.475890e-01 3.280889e-01 5.503374e-01
## 56 1.951405e-01 7.399778e-02 7.884323e-01 4.358399e-01 2.208251e-01
## 57 1.800439e-01 5.890215e-02 7.733366e-01 4.210509e-01 2.057286e-01
## 58 3.288550e-01 2.076979e-01 9.221534e-01 5.680862e-01 3.545406e-01
## 59 3.925158e-01 5.136730e-01 2.007825e-01 1.790164e-01 3.668302e-01
## 60 3.085889e+00 3.089825e+00 3.134899e+00 3.010021e+00 3.085666e+00
## 61 2.199085e-01 3.410656e-01 3.733899e-01 8.293421e-02 1.942228e-01
## 62 1.469014e-01 2.670478e-01 4.493538e-01 1.050226e-01 1.216878e-01
## 63 1.655083e-01 2.866596e-01 4.278093e-01 1.046447e-01 1.398253e-01
## 64 2.077769e-01 8.661983e-02 8.010753e-01 4.486106e-01 2.334626e-01
## 65 5.769386e-02 6.346325e-02 6.509922e-01 3.022891e-01 8.337949e-02
## 66 1.006316e-01 2.089123e-02 6.938765e-01 3.429319e-01 1.263045e-01
## 67 1.877817e-01 3.089388e-01 4.055167e-01 9.365339e-02 1.620960e-01
## 68 5.769386e-02 6.346325e-02 6.509922e-01 3.022891e-01 8.337949e-02
## 69 8.282626e-02 2.039834e-01 5.104721e-01 1.712960e-01 5.714063e-02
## 70 1.299693e-01 2.511264e-01 4.633291e-01 1.318211e-01 1.042836e-01
## 71 2.541490e-01 3.708468e-01 3.623757e-01 7.135230e-03 2.300021e-01
## 72 1.603546e-01 6.689865e-02 7.440436e-01 3.820897e-01 1.843581e-01
## 73 1.508339e-01 2.719910e-01 4.424645e-01 1.161896e-01 1.251483e-01
## 74 1.738719e-01 5.271480e-02 7.671703e-01 4.153207e-01 1.995575e-01
## 75 4.679525e-01 5.891097e-01 1.253458e-01 2.485122e-01 4.422669e-01
## 76 1.191023e-01 2.054850e-03 7.124006e-01 3.617861e-01 1.447879e-01
## 77 2.297480e-01 1.085909e-01 8.230464e-01 4.702300e-01 2.554336e-01
## 78 1.895229e-01 3.106790e-01 4.037792e-01 9.196718e-02 1.638376e-01
## 79 5.955643e-02 1.804714e-01 5.341430e-01 1.896939e-01 3.414343e-02
## 80 2.469213e-01 1.259006e-01 8.401196e-01 4.856749e-01 2.725935e-01
## 81 2.983484e-02 9.132227e-02 6.231332e-01 2.755738e-01 5.552046e-02
## 82 5.927452e-02 1.804316e-01 5.340239e-01 1.923150e-01 3.358889e-02
## 83 7.021658e-02 7.156728e-02 6.541237e-01 2.965309e-01 9.306726e-02
## 84 2.913004e-01 4.123920e-01 3.024358e-01 9.110776e-02 2.656364e-01
## 85 1.640719e-01 2.852290e-01 4.292265e-01 1.071998e-01 1.383862e-01
## 86 8.527214e-01 8.541575e-01 1.067247e+00 8.200439e-01 8.546261e-01
## 87 1.384258e-01 2.595829e-01 4.548726e-01 1.253021e-01 1.127401e-01
## 88 1.077205e-01 1.185538e-01 6.507574e-01 2.840795e-01 1.218842e-01
## 89 4.386721e-01 5.597092e-01 1.567391e-01 2.133641e-01 4.130210e-01
## 90 1.048564e+00 1.028832e+00 1.313053e+00 1.048976e+00 1.054490e+00
## 91 1.051135e-01 1.604364e-02 6.984119e-01 3.481743e-01 1.307991e-01
## 92 2.047342e-01 3.258913e-01 3.885642e-01 8.668848e-02 1.790486e-01
## 93 3.258123e-01 2.046551e-01 9.191106e-01 5.650754e-01 3.514979e-01
## 94 7.326330e-02 1.944204e-01 5.200351e-01 1.797549e-01 4.757768e-02
## 95 1.195369e-01 1.620170e-03 7.128353e-01 3.622095e-01 1.452226e-01
## 96 8.713354e-02 3.402357e-02 6.804319e-01 3.307252e-01 1.128192e-01
## 97 1.272426e-01 2.483997e-01 4.660558e-01 1.339692e-01 1.015570e-01
## 98 1.027425e-03 1.221845e-01 5.922710e-01 2.462748e-01 2.465820e-02
## 99 3.611794e-02 8.503917e-02 6.294163e-01 2.815796e-01 6.180356e-02
## 100 2.619414e-01 3.793727e-01 3.517229e-01 1.746502e-02 2.375270e-01
## 101 9.816872e-01 1.044681e+00 8.732153e-01 8.160176e-01 9.697523e-01
## 102 1.501621e-01 2.713192e-01 4.431363e-01 1.166674e-01 1.244765e-01
## 103 8.650128e-02 2.076584e-01 5.067971e-01 1.680768e-01 6.081565e-02
## 104 9.404890e-02 2.152060e-01 4.992495e-01 1.615263e-01 6.836327e-02
## 105 1.426935e-01 2.153641e-02 7.359919e-01 3.848027e-01 1.683791e-01
## 106 1.755313e-01 2.767163e-01 4.802181e-01 1.116902e-01 1.577390e-01
## 107 5.413739e-02 6.701972e-02 6.474358e-01 2.988670e-01 7.982301e-02
## 108 1.267684e-01 2.479255e-01 4.665300e-01 1.343449e-01 1.010828e-01
## 109 5.321127e-01 6.532359e-01 6.293723e-02 3.062433e-01 5.064364e-01
## 110 3.284994e-01 4.496565e-01 2.647990e-01 1.255416e-01 3.028137e-01
## 111 1.604759e-01 2.816330e-01 4.328225e-01 1.095565e-01 1.347902e-01
## 112 1.459734e-01 2.481626e-02 7.392718e-01 3.880082e-01 1.716590e-01
## 113 7.002296e-02 5.113415e-02 6.633213e-01 3.141754e-01 9.570858e-02
## 114 1.125805e-01 2.337179e-01 4.807647e-01 1.442637e-01 8.690612e-02
## 115 1.547455e-01 2.756251e-01 4.394067e-01 1.042993e-01 1.291856e-01
## 116 4.756119e-02 1.685598e-01 5.459770e-01 2.013781e-01 2.213309e-02
## 117 2.976371e-01 4.187942e-01 2.956613e-01 1.041024e-01 2.719515e-01
## 118 2.135068e-01 3.346639e-01 3.797916e-01 8.420557e-02 1.878212e-01
## 119 2.576466e-01 3.788037e-01 3.356518e-01 8.538832e-02 2.319609e-01
## 120 1.918914e-01 7.073426e-02 7.851898e-01 4.330013e-01 2.175770e-01
## 121 4.797284e-02 7.318427e-02 6.412712e-01 2.929429e-01 7.365846e-02
## 122 1.465266e-01 2.676837e-01 4.467718e-01 1.192855e-01 1.208410e-01
## 123 5.717620e-01 6.929191e-01 2.153641e-02 3.482127e-01 5.460764e-01
## 124 6.855703e-01 8.064126e-01 1.048844e-01 4.510577e-01 6.599662e-01
## 125 3.810956e-01 5.022527e-01 2.122028e-01 1.689404e-01 3.554100e-01
## 126 1.907059e-01 6.954877e-02 7.840043e-01 4.318373e-01 2.163915e-01
## 127 4.973752e-02 1.702868e-01 5.444942e-01 1.982195e-01 2.494910e-02
## 128 6.834747e-01 8.046318e-01 9.017630e-02 4.575498e-01 6.577891e-01
## 129 1.016935e+00 1.138047e+00 4.242188e-01 7.849884e-01 9.912598e-01
## 130 1.122264e-02 1.099345e-01 6.045210e-01 2.578607e-01 3.690827e-02
## 131 8.388144e-02 6.548255e-02 6.666174e-01 3.076648e-01 1.067261e-01
## 132 1.550226e-01 2.761797e-01 4.382758e-01 1.132549e-01 1.293370e-01
## 133 2.640107e-01 1.566659e-01 8.454112e-01 4.803811e-01 2.881786e-01
## 134 8.958355e-02 3.157356e-02 6.828819e-01 3.330996e-01 1.152692e-01
## 135 2.781555e-01 1.569984e-01 8.714539e-01 5.179672e-01 3.038412e-01
## 136 4.261838e-01 5.473409e-01 1.671146e-01 2.095258e-01 4.004981e-01
## 137 5.204302e-02 1.732001e-01 5.412554e-01 1.988828e-01 2.635740e-02
## 138 1.548646e-01 3.370744e-02 7.481629e-01 3.967037e-01 1.805502e-01
## 139 2.223190e-01 1.011618e-01 8.156173e-01 4.629161e-01 2.480046e-01
## 140 1.271488e+00 1.306466e+00 1.264518e+00 1.153541e+00 1.265440e+00
## 141 2.031600e-01 3.242261e-01 3.905086e-01 7.805871e-02 1.775096e-01
## 142 1.417546e-01 2.627799e-01 4.519195e-01 1.172175e-01 1.161323e-01
## 143 2.474524e-01 3.686091e-01 3.458478e-01 8.235993e-02 2.217669e-01
## 144 9.448820e-02 2.722273e-02 6.876803e-01 3.366003e-01 1.201475e-01
## 145 1.948077e-01 3.154522e-01 4.004744e-01 7.124698e-02 1.693248e-01
## 146 4.022707e-01 5.185033e-01 2.482295e-01 1.550690e-01 3.780266e-01
## 147 1.365246e-02 1.307170e-01 5.842182e-01 2.353344e-01 1.936957e-02
## 148 1.252493e-01 5.626679e-03 7.184969e-01 3.668625e-01 1.509245e-01
## 149 3.456711e-01 4.649111e-01 2.647008e-01 1.055528e-01 3.205767e-01
## 150 3.939521e-02 1.423456e-01 5.777666e-01 2.215254e-01 3.683887e-02
## 151 1.495184e-01 3.255959e-02 7.419733e-01 3.871130e-01 1.750492e-01
## 152 4.799655e-01 6.011226e-01 1.133329e-01 2.598851e-01 4.542799e-01
## 153 5.560685e-02 1.586296e-01 5.647088e-01 2.058564e-01 4.674088e-02
## 154 3.465583e-02 8.650128e-02 6.279542e-01 2.801810e-01 6.034146e-02
## 155 2.488344e-01 3.699915e-01 3.444640e-01 8.330551e-02 2.231488e-01
## 156 2.658524e-01 2.950448e-01 6.437243e-01 2.916180e-01 2.664169e-01
## 157 1.670751e-01 4.591799e-02 7.603735e-01 4.086593e-01 1.927607e-01
## 158 1.227773e-01 1.620170e-03 7.160757e-01 3.653667e-01 1.484629e-01
## 159 5.283335e-02 6.832376e-02 6.461317e-01 2.976130e-01 7.851898e-02
## 160 2.683160e-02 9.432551e-02 6.201300e-01 2.727076e-01 5.251722e-02
## 161 2.467796e-01 1.256225e-01 8.400780e-01 4.870106e-01 2.724652e-01
## 162 3.125348e-01 1.913777e-01 9.058331e-01 5.519412e-01 3.382204e-01
## 163 1.736348e-01 2.947919e-01 4.196636e-01 1.012872e-01 1.479492e-01
## 164 1.751364e-01 2.962935e-01 4.181620e-01 1.004099e-01 1.494508e-01
## 165 1.545484e-01 2.757055e-01 4.387500e-01 1.135832e-01 1.288628e-01
## 166 8.310287e-02 2.042600e-01 5.101955e-01 1.710531e-01 5.741725e-02
## 167 3.657077e-01 3.852547e-01 6.969541e-01 3.674356e-01 3.666086e-01
## 168 1.609518e-01 2.785386e-01 4.435376e-01 8.634849e-02 1.368258e-01
## 169 2.576284e-02 9.624141e-02 6.184188e-01 2.693444e-01 5.111289e-02
## 170 4.288709e-01 5.500280e-01 1.644275e-01 2.120020e-01 4.031853e-01
## 171 2.469994e-01 1.737400e-01 7.973913e-01 4.283614e-01 2.670488e-01
## 172 2.997391e-02 1.495861e-01 5.653402e-01 2.172786e-01 1.081127e-02
## 173 2.838557e-01 4.047498e-01 3.111238e-01 7.752467e-02 2.582576e-01
## 174 7.853187e-02 1.737581e-01 5.589326e-01 1.951995e-01 6.961122e-02
## 175 1.911746e-01 9.010238e-02 7.743703e-01 4.113780e-01 2.152825e-01
## 176 8.231701e-02 1.111689e-01 6.350784e-01 2.709811e-01 9.676954e-02
## 177 1.665285e-01 2.394752e-01 5.537024e-01 1.864789e-01 1.588228e-01
## 178 1.904688e-01 6.931167e-02 7.837672e-01 4.316045e-01 2.161544e-01
## 179 1.794993e-01 6.141313e-02 7.716316e-01 4.154331e-01 2.049949e-01
## 180 5.468272e-01 6.679843e-01 4.647122e-02 3.240295e-01 5.211415e-01
## 181 1.040860e-01 1.707106e-02 6.973844e-01 3.471758e-01 1.297717e-01
## 182 1.114361e-01 2.325932e-01 4.818623e-01 1.468010e-01 8.575047e-02
## 183 1.833698e-01 3.043641e-01 4.105203e-01 8.590184e-02 1.577508e-01
## 184 4.212640e-01 5.292283e-01 3.143706e-01 1.850366e-01 3.993489e-01
## 185 2.942080e-01 4.153626e-01 2.991079e-01 1.001911e-01 2.685233e-01
## 186 3.012910e-01 4.220119e-01 2.950796e-01 8.415661e-02 2.757470e-01
## 187 4.059049e-02 8.779976e-02 6.291673e-01 2.759884e-01 6.429886e-02
## 188 2.748196e-01 1.949111e-01 8.265711e-01 4.574728e-01 2.953898e-01
## 189 2.888384e-01 1.678907e-01 8.819417e-01 5.263823e-01 3.145003e-01
## 190 1.762985e+00 1.786776e+00 1.765908e+00 1.658365e+00 1.758972e+00
## 191 1.645222e-01 2.856224e-01 4.289619e-01 1.020025e-01 1.388615e-01
## 192 2.030745e-01 8.191738e-02 7.963729e-01 4.439879e-01 2.287601e-01
## 193 1.171660e-01 2.383231e-01 4.761324e-01 1.420802e-01 9.148034e-02
## 194 1.917542e-01 7.210878e-02 7.843795e-01 4.288788e-01 2.173346e-01
## 195 3.347114e-01 2.176228e-01 9.233698e-01 5.609181e-01 3.598807e-01
## 196 4.356515e-01 3.166274e-01 1.025741e+00 6.635180e-01 4.610277e-01
## 197 2.947026e-01 3.015121e-01 7.006094e-01 3.474538e-01 2.996008e-01
## 198 1.278749e-01 6.717778e-03 7.211733e-01 3.703366e-01 1.535605e-01
## 199 4.619461e-02 7.496250e-02 6.394930e-01 2.912359e-01 7.188023e-02
## 200 2.909984e-01 4.121555e-01 3.023000e-01 1.001360e-01 2.653127e-01
## 201 2.347271e-02 1.446298e-01 5.698257e-01 2.252288e-01 2.212915e-03
## 202 1.934674e-02 1.018850e-01 6.125843e-01 2.650417e-01 4.499655e-02
## 203 1.135470e-01 4.259370e-02 7.007353e-01 3.421818e-01 1.378891e-01
## 204 3.078009e-01 2.616063e-01 8.046325e-01 4.389673e-01 3.226291e-01
## 205 3.280899e-01 3.372289e-01 7.083453e-01 3.632361e-01 3.318519e-01
## 206 4.617121e-01 3.405561e-01 1.055009e+00 6.996198e-01 4.873975e-01
## 207 2.758475e-01 1.582579e-01 8.659951e-01 5.055357e-01 3.011404e-01
## 208 3.548568e-02 1.566428e-01 5.578127e-01 2.140816e-01 9.800053e-03
## 209 2.347271e-02 1.446298e-01 5.698257e-01 2.252288e-01 2.212915e-03
## 210 2.781540e-01 1.805679e-01 8.488024e-01 4.811504e-01 3.010509e-01
## 211 2.518364e-01 3.721586e-01 3.458940e-01 4.867034e-02 2.264422e-01
## 212 8.650128e-02 2.076584e-01 5.067971e-01 1.680768e-01 6.081565e-02
## 213 1.327922e-01 2.396435e-01 4.966330e-01 1.296583e-01 1.138808e-01
## 214 1.965543e-01 7.539718e-02 7.898527e-01 4.375811e-01 2.222399e-01
## 215 5.524499e-02 1.759393e-01 5.387949e-01 1.931597e-01 3.013843e-02
## 216 5.311787e-01 6.523358e-01 6.211969e-02 3.089137e-01 5.054931e-01
## 217 1.495298e-01 2.706870e-01 4.437685e-01 1.171188e-01 1.238442e-01
## 218 3.526110e-01 2.331474e-01 9.438706e-01 5.836656e-01 3.780761e-01
## 219 1.082748e-01 1.288233e-02 7.015732e-01 3.512478e-01 1.339604e-01
## 220 7.331076e-01 7.684674e-01 8.374528e-01 6.383083e-01 7.279850e-01
## 221 3.525660e-01 4.704166e-01 2.706282e-01 1.071208e-01 3.278912e-01
## 222 1.352968e-01 3.413653e-02 7.253437e-01 3.679290e-01 1.603455e-01
## 223 1.377935e-01 1.663638e-02 7.310919e-01 3.800162e-01 1.634791e-01
## 224 4.686638e-02 1.680235e-01 5.464320e-01 2.036119e-01 2.118076e-02
## 225 5.635648e-01 5.837206e-01 7.926230e-01 5.199985e-01 5.625607e-01
## 226 1.702332e-01 4.955358e-02 7.633805e-01 4.100237e-01 1.958933e-01
## 16 17 18 19 20
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17 9.783245e-01
## 18 1.014480e+00 6.189871e-01
## 19 1.041463e+00 2.242048e-01 8.426287e-01
## 20 1.022489e+00 1.481490e-01 7.670872e-01 7.669307e-02
## 21 1.006701e+00 1.015602e-01 7.205176e-01 1.229420e-01 4.658977e-02
## 22 3.795707e-01 1.136252e+00 1.330903e+00 1.124403e+00 1.131453e+00
## 23 1.156190e+00 4.717807e-01 1.089713e+00 2.475837e-01 3.240224e-01
## 24 9.494710e-01 5.052044e-02 6.520055e-01 1.927152e-01 1.214027e-01
## 25 8.984603e-01 1.743199e-01 7.491902e-01 1.503719e-01 1.261350e-01
## 26 1.090058e+00 3.078334e-01 9.267190e-01 8.470783e-02 1.596855e-01
## 27 1.002093e+00 8.678165e-02 7.057455e-01 1.376610e-01 6.136888e-02
## 28 1.028255e+00 1.639158e-01 7.828480e-01 6.115870e-02 1.576702e-02
## 29 9.666008e-01 4.469921e-02 5.743064e-01 2.686768e-01 1.927937e-01
## 30 9.564563e-01 1.549852e-01 4.641612e-01 3.791034e-01 3.031299e-01
## 31 8.670237e-01 2.773023e-01 3.617008e-01 4.930407e-01 4.206435e-01
## 32 9.694308e-01 1.516970e-01 7.611928e-01 9.257194e-02 5.489597e-02
## 33 9.601420e-01 1.133357e-01 5.057690e-01 3.374755e-01 2.614796e-01
## 34 1.060464e+00 2.435010e-01 8.624057e-01 2.280271e-02 9.535294e-02
## 35 9.757147e-01 1.574821e-02 6.032977e-01 2.399530e-01 1.638743e-01
## 36 9.760617e-01 1.409097e-02 6.049563e-01 2.382953e-01 1.622146e-01
## 37 1.071271e+00 2.993148e-01 9.175456e-01 7.511667e-02 1.516583e-01
## 38 1.090153e+00 3.080310e-01 9.269165e-01 8.490351e-02 1.598831e-01
## 39 1.007039e+00 1.925874e-01 8.084361e-01 4.079614e-02 5.365916e-02
## 40 9.665964e-01 6.536502e-02 5.537008e-01 2.895364e-01 2.135068e-01
## 41 9.603084e-01 1.118342e-01 5.072692e-01 3.359748e-01 2.599780e-01
## 42 9.980069e-01 7.310969e-02 6.920795e-01 1.512885e-01 7.504154e-02
## 43 1.014499e+00 1.252694e-01 7.442169e-01 9.936585e-02 2.287996e-02
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## 58 1.155855e+00 4.331789e-01 1.052034e+00 2.095670e-01 2.850314e-01
## 59 9.568222e-01 2.881938e-01 3.311592e-01 5.122659e-01 4.363395e-01
## 60 2.150101e+00 3.085503e+00 3.139013e+00 3.078041e+00 3.086764e+00
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## 64 1.092127e+00 3.121011e-01 9.309856e-01 8.893651e-02 1.639533e-01
## 65 1.027550e+00 1.620190e-01 7.809519e-01 6.302138e-02 1.387024e-02
## 66 1.040966e+00 2.049105e-01 8.237246e-01 2.072638e-02 5.685618e-02
## 67 9.638860e-01 8.346242e-02 5.356169e-01 3.076210e-01 2.316053e-01
## 68 1.027550e+00 1.620190e-01 7.809519e-01 6.302138e-02 1.387024e-02
## 69 9.841418e-01 2.151205e-02 6.404991e-01 2.027812e-01 1.266499e-01
## 70 9.736970e-01 2.565881e-02 5.933858e-01 2.498602e-01 1.737929e-01
## 71 8.758345e-01 1.586834e-01 4.863157e-01 3.669074e-01 2.959462e-01
## 72 1.009957e+00 2.596643e-01 8.720632e-01 5.713700e-02 1.210063e-01
## 73 9.697703e-01 4.651774e-02 5.725358e-01 2.707037e-01 1.946575e-01
## 74 1.076048e+00 2.781962e-01 8.970903e-01 5.550724e-02 1.300483e-01
## 75 9.652175e-01 3.636303e-01 2.559359e-01 5.876854e-01 5.117762e-01
## 76 1.051865e+00 2.234269e-01 8.423380e-01 1.173077e-02 7.527863e-02
## 77 1.102977e+00 3.340721e-01 9.529507e-01 1.107539e-01 1.859244e-01
## 78 9.626833e-01 8.519739e-02 5.338408e-01 3.093232e-01 2.333460e-01
## 79 9.838725e-01 4.549120e-02 6.639331e-01 1.788863e-01 1.032269e-01
## 80 1.104442e+00 3.511840e-01 9.698253e-01 1.272078e-01 2.031282e-01
## 81 1.017550e+00 1.341604e-01 7.531042e-01 9.054280e-02 1.398879e-02
## 82 9.901597e-01 4.505587e-02 6.640375e-01 1.792740e-01 1.030981e-01
## 83 9.942529e-01 1.680163e-01 7.828823e-01 6.487996e-02 4.013234e-02
## 84 9.434669e-01 1.870542e-01 4.320013e-01 4.106935e-01 3.350949e-01
## 85 9.675039e-01 5.975417e-02 5.593078e-01 2.839298e-01 2.078955e-01
## 86 3.877019e-01 8.643911e-01 1.134013e+00 8.423509e-01 8.512528e-01
## 87 9.720535e-01 3.411216e-02 5.849351e-01 2.583077e-01 1.822494e-01
## 88 9.369180e-01 1.812810e-01 7.768787e-01 1.083796e-01 9.540086e-02
## 89 9.393127e-01 3.344696e-01 2.848339e-01 5.578293e-01 4.824454e-01
## 90 5.572907e-01 1.075479e+00 1.382045e+00 1.017344e+00 1.039842e+00
## 91 1.046059e+00 2.094382e-01 8.283540e-01 1.864590e-02 6.128985e-02
## 92 9.616494e-01 1.004143e-01 5.186790e-01 3.245618e-01 2.485578e-01
## 93 1.154141e+00 4.301362e-01 1.048992e+00 2.065291e-01 2.819886e-01
## 94 9.865220e-01 3.107034e-02 6.500565e-01 1.932350e-01 1.170869e-01
## 95 1.052048e+00 2.238615e-01 8.427725e-01 1.171978e-02 7.571331e-02
## 96 1.038825e+00 1.914584e-01 8.103805e-01 3.453195e-02 4.330991e-02
## 97 9.742420e-01 2.293370e-02 5.961105e-01 2.471366e-01 1.710663e-01
## 98 1.007256e+00 1.032989e-01 7.222556e-01 1.212113e-01 4.485105e-02
## 99 1.019747e+00 1.404434e-01 7.593847e-01 8.431648e-02 7.705687e-03
## 100 8.798644e-01 1.648187e-01 4.759936e-01 3.756360e-01 3.040801e-01
## 101 1.691172e-01 9.359086e-01 8.803086e-01 1.034137e+00 1.003241e+00
## 102 9.698900e-01 4.584607e-02 5.732071e-01 2.700325e-01 1.939857e-01
## 103 9.832504e-01 1.784015e-02 6.368262e-01 2.064502e-01 1.303249e-01
## 104 9.814601e-01 1.030592e-02 6.292831e-01 2.139860e-01 1.378725e-01
## 105 1.062003e+00 2.470180e-01 8.659215e-01 2.588282e-02 9.886989e-02
## 106 8.569728e-01 1.214028e-01 6.026934e-01 2.704335e-01 2.097004e-01
## 107 1.026237e+00 1.584626e-01 7.773969e-01 6.651911e-02 1.031377e-02
## 108 9.743376e-01 2.245980e-02 5.965844e-01 2.466630e-01 1.705921e-01
## 109 9.632208e-01 4.278087e-01 1.911860e-01 6.515493e-01 5.759224e-01
## 110 9.543285e-01 2.241777e-01 3.950585e-01 4.482686e-01 3.723230e-01
## 111 9.681022e-01 5.615853e-02 5.629010e-01 2.803369e-01 2.042995e-01
## 112 1.063446e+00 2.502978e-01 8.692003e-01 2.884545e-02 1.021497e-01
## 113 1.032185e+00 1.743480e-01 7.932763e-01 5.095894e-02 2.619934e-02
## 114 9.744512e-01 8.487529e-03 6.107032e-01 2.323251e-01 1.563935e-01
## 115 9.554410e-01 5.150078e-02 5.688928e-01 2.737390e-01 1.984297e-01
## 116 9.890135e-01 5.710703e-02 6.758325e-01 1.671093e-01 9.127896e-02
## 117 9.546588e-01 1.933156e-01 4.258768e-01 4.174176e-01 3.414607e-01
## 118 9.606074e-01 1.091866e-01 5.099143e-01 3.333289e-01 2.573304e-01
## 119 9.565688e-01 1.533255e-01 4.658191e-01 3.774445e-01 3.014702e-01
## 120 1.084491e+00 2.962156e-01 9.151045e-01 7.321939e-02 1.480677e-01
## 121 1.023986e+00 1.522981e-01 7.712348e-01 7.259535e-02 4.149216e-03
## 122 9.705455e-01 4.221118e-02 5.768400e-01 2.664005e-01 1.903502e-01
## 123 9.861325e-01 4.674395e-01 1.527645e-01 6.914773e-01 6.155856e-01
## 124 9.700985e-01 5.815493e-01 5.061871e-02 8.041800e-01 7.292680e-01
## 125 9.560638e-01 2.767736e-01 3.425553e-01 5.008487e-01 4.249192e-01
## 126 1.083928e+00 2.950301e-01 9.139193e-01 7.204944e-02 1.468822e-01
## 127 9.841554e-01 5.607110e-02 6.741893e-01 1.685167e-01 9.315943e-02
## 128 1.020026e+00 5.791521e-01 4.513457e-02 8.031762e-01 7.272983e-01
## 129 1.156118e+00 9.126337e-01 2.936555e-01 1.136267e+00 1.060741e+00
## 130 1.011242e+00 1.155486e-01 7.345001e-01 1.090250e-01 3.260098e-02
## 131 9.931612e-01 1.812626e-01 7.951563e-01 5.713196e-02 5.150766e-02
## 132 9.690342e-01 5.070590e-02 5.683502e-01 2.748885e-01 1.988462e-01
## 133 1.032631e+00 3.632594e-01 9.725225e-01 1.512693e-01 2.235593e-01
## 134 1.039795e+00 1.939084e-01 8.128296e-01 3.223807e-02 4.575993e-02
## 135 1.128027e+00 3.824795e-01 1.001346e+00 1.589721e-01 2.343319e-01
## 136 9.598459e-01 3.218616e-01 2.975732e-01 5.459255e-01 4.700074e-01
## 137 9.921123e-01 5.228636e-02 6.712652e-01 1.720586e-01 9.586665e-02
## 138 1.067399e+00 2.591890e-01 8.780887e-01 3.714579e-02 1.110409e-01
## 139 1.099271e+00 3.266431e-01 9.455236e-01 1.033695e-01 1.784953e-01
## 140 2.786623e-01 1.249229e+00 1.278832e+00 1.294900e+00 1.282930e+00
## 141 9.520098e-01 9.901575e-02 5.201720e-01 3.225373e-01 2.469404e-01
## 142 9.626378e-01 3.803857e-02 5.816256e-01 2.610986e-01 1.855107e-01
## 143 9.566153e-01 1.431282e-01 4.759712e-01 3.672324e-01 2.912758e-01
## 144 1.037287e+00 1.987288e-01 8.174945e-01 2.617580e-02 5.077100e-02
## 145 9.405423e-01 9.181511e-02 5.294802e-01 3.132831e-01 2.383859e-01
## 146 8.275422e-01 3.049320e-01 3.581845e-01 5.142164e-01 4.440093e-01
## 147 9.950769e-01 9.560962e-02 7.138806e-01 1.287937e-01 5.394842e-02
## 148 1.050887e+00 2.295321e-01 8.483293e-01 9.580417e-03 8.145881e-02
## 149 8.834346e-01 2.442804e-01 3.877767e-01 4.617375e-01 3.886644e-01
## 150 9.684347e-01 9.437781e-02 7.064505e-01 1.383483e-01 7.021841e-02
## 151 1.048678e+00 2.533522e-01 8.714243e-01 2.946741e-02 1.061315e-01
## 152 9.670910e-01 3.756432e-01 2.439691e-01 5.996960e-01 5.237891e-01
## 153 9.538659e-01 8.680972e-02 6.928822e-01 1.540970e-01 8.767242e-02
## 154 1.019233e+00 1.389813e-01 7.579232e-01 8.576463e-02 9.167792e-03
## 155 9.572138e-01 1.445135e-01 4.746217e-01 3.686367e-01 2.926580e-01
## 156 7.577235e-01 2.822641e-01 7.563548e-01 2.838432e-01 2.705754e-01
## 157 1.072924e+00 2.713995e-01 8.902955e-01 4.888472e-02 1.232515e-01
## 158 1.053416e+00 2.271019e-01 8.460118e-01 1.213841e-02 7.895365e-02
## 159 1.025758e+00 1.571586e-01 7.760933e-01 6.780314e-02 9.009726e-03
## 160 1.016512e+00 1.311572e-01 7.501023e-01 9.352159e-02 1.699203e-02
## 161 1.111615e+00 3.511036e-01 9.699779e-01 1.277025e-01 2.029559e-01
## 162 1.146726e+00 4.168587e-01 1.035717e+00 1.932744e-01 2.687111e-01
## 163 9.659763e-01 6.931637e-02 5.497523e-01 2.934849e-01 2.174584e-01
## 164 9.657448e-01 7.081789e-02 5.482518e-01 2.949853e-01 2.189601e-01
## 165 9.691166e-01 5.023176e-02 5.688240e-01 2.744148e-01 1.983720e-01
## 166 9.840743e-01 2.123563e-02 6.402226e-01 2.030573e-01 1.269265e-01
## 167 6.715428e-01 3.795202e-01 8.005478e-01 3.736517e-01 3.683241e-01
## 168 9.193788e-01 6.963347e-02 5.709984e-01 2.751115e-01 2.029999e-01
## 169 1.010433e+00 1.295137e-01 7.482164e-01 9.470596e-02 1.961919e-02
## 170 9.601377e-01 3.245487e-01 2.948934e-01 5.486120e-01 4.726945e-01
## 171 9.441372e-01 3.328867e-01 9.212160e-01 1.636145e-01 2.155706e-01
## 172 9.888646e-01 7.688607e-02 6.949873e-01 1.476772e-01 7.265005e-02
## 173 9.328614e-01 1.799444e-01 4.399752e-01 4.027322e-01 3.275618e-01
## 174 9.305327e-01 9.430643e-02 6.859634e-01 1.680352e-01 1.070894e-01
## 175 1.016474e+00 2.905811e-01 9.021378e-01 8.241725e-02 1.512467e-01
## 176 9.520783e-01 1.592936e-01 7.622256e-01 1.025837e-01 7.352738e-02
## 177 8.413322e-01 1.596991e-01 6.745120e-01 2.308650e-01 1.872306e-01
## 178 1.083816e+00 2.947930e-01 9.136823e-01 7.181551e-02 1.466452e-01
## 179 1.057387e+00 2.831988e-01 9.009342e-01 5.950198e-02 1.361650e-01
## 180 9.801467e-01 4.425048e-01 1.774782e-01 6.665462e-01 5.906508e-01
## 181 1.045639e+00 2.084108e-01 8.273269e-01 1.945573e-02 6.026242e-02
## 182 9.775453e-01 7.158616e-03 6.119067e-01 2.313491e-01 1.552597e-01
## 183 9.524657e-01 7.946450e-02 5.400768e-01 3.025771e-01 2.271145e-01
## 184 7.414729e-01 3.350827e-01 4.080398e-01 5.231794e-01 4.595570e-01
## 185 9.524751e-01 1.898818e-01 4.291999e-01 4.139227e-01 3.380305e-01
## 186 9.243873e-01 1.976495e-01 4.232628e-01 4.197951e-01 3.449215e-01
## 187 1.001264e+00 1.411397e-01 7.585198e-01 8.441651e-02 2.123557e-02
## 188 9.510671e-01 3.620690e-01 9.501403e-01 1.855340e-01 2.419914e-01
## 189 1.122730e+00 3.930588e-01 1.011539e+00 1.689368e-01 2.450666e-01
## 190 7.857896e-01 1.748173e+00 1.771662e+00 1.775016e+00 1.770671e+00
## 191 9.608976e-01 6.034787e-02 5.587712e-01 2.840493e-01 2.083176e-01
## 192 1.089848e+00 3.073987e-01 9.262844e-01 8.427735e-02 1.592509e-01
## 193 9.763196e-01 1.286816e-02 6.061805e-01 2.370718e-01 1.609896e-01
## 194 1.067791e+00 2.957142e-01 9.138219e-01 7.156575e-02 1.481941e-01
## 195 1.098564e+00 4.371839e-01 1.051490e+00 2.156675e-01 2.919764e-01
## 196 1.162212e+00 5.387969e-01 1.154024e+00 3.157837e-01 3.924487e-01
## 197 7.577521e-01 3.262003e-01 8.127727e-01 2.897934e-01 2.914260e-01
## 198 1.055585e+00 2.321994e-01 8.511077e-01 1.433725e-02 8.405126e-02
## 199 1.023342e+00 1.505199e-01 7.694572e-01 7.435082e-02 2.370981e-03
## 200 9.548602e-01 1.866770e-01 4.325069e-01 4.107815e-01 3.348220e-01
## 201 1.000301e+00 8.085447e-02 6.998209e-01 1.435678e-01 6.729633e-02
## 202 1.012471e+00 1.236094e-01 7.425136e-01 1.008453e-01 2.458900e-02
## 203 1.010278e+00 2.142226e-01 8.294466e-01 3.118502e-02 7.413924e-02
## 204 8.535108e-01 3.748312e-01 9.225893e-01 2.503949e-01 2.860736e-01
## 205 7.233853e-01 3.541246e-01 8.172006e-01 3.255057e-01 3.262717e-01
## 206 1.234381e+00 5.660328e-01 1.184832e+00 3.422398e-01 4.178888e-01
## 207 1.082067e+00 3.787981e-01 9.945951e-01 1.564324e-01 2.328925e-01
## 208 9.967663e-01 6.884221e-02 6.878139e-01 1.555438e-01 7.930930e-02
## 209 1.000301e+00 8.085447e-02 6.998209e-01 1.435678e-01 6.729633e-02
## 210 1.000489e+00 3.731306e-01 9.744103e-01 1.733614e-01 2.403929e-01
## 211 9.214240e-01 1.491260e-01 4.738889e-01 3.696746e-01 2.952792e-01
## 212 9.832504e-01 1.784015e-02 6.368262e-01 2.064502e-01 1.303249e-01
## 213 8.985624e-01 8.220244e-02 6.223096e-01 2.343720e-01 1.692308e-01
## 214 1.086714e+00 3.008785e-01 9.197661e-01 7.782578e-02 1.527307e-01
## 215 9.831520e-01 5.035711e-02 6.685114e-01 1.742160e-01 9.877050e-02
## 216 9.766966e-01 4.268563e-01 1.930169e-01 6.509002e-01 5.750023e-01
## 217 9.700030e-01 4.521391e-02 5.738389e-01 2.694009e-01 1.933535e-01
## 218 1.128861e+00 4.561085e-01 1.072627e+00 2.325550e-01 3.092479e-01
## 219 1.047358e+00 2.125995e-01 8.315142e-01 1.630858e-02 6.445116e-02
## 220 2.899116e-01 7.170051e-01 8.944443e-01 7.569961e-01 7.438164e-01
## 221 8.600321e-01 2.532998e-01 3.900769e-01 4.666878e-01 3.949627e-01
## 222 1.027731e+00 2.377698e-01 8.543315e-01 2.392549e-02 9.336232e-02
## 223 1.059862e+00 2.421180e-01 8.610230e-01 2.162797e-02 9.396987e-02
## 224 9.935401e-01 5.746244e-02 6.764391e-01 1.668943e-01 9.069001e-02
## 225 4.865399e-01 5.659584e-01 8.750625e-01 5.720179e-01 5.679618e-01
## 226 1.067065e+00 2.744597e-01 8.930961e-01 5.055029e-02 1.264769e-01
## 21 22 23 24 25
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22 1.131128e+00
## 23 3.704745e-01 1.159789e+00
## 24 7.870362e-02 1.095307e+00 4.380932e-01
## 25 1.256744e-01 1.007320e+00 3.607824e-01 1.239855e-01
## 26 2.062753e-01 1.147014e+00 1.653973e-01 2.774227e-01 2.219161e-01
## 27 1.477911e-02 1.131426e+00 3.852169e-01 6.626324e-02 1.290900e-01
## 28 6.235679e-02 1.131997e+00 3.083114e-01 1.364309e-01 1.301248e-01
## 29 1.462145e-01 1.138976e+00 5.162031e-01 8.542969e-02 2.067275e-01
## 30 2.565401e-01 1.163259e+00 6.266229e-01 1.921223e-01 3.048284e-01
## 31 3.752223e-01 1.109722e+00 7.367706e-01 3.003589e-01 3.883157e-01
## 32 6.781385e-02 1.076776e+00 3.303925e-01 1.098242e-01 7.155773e-02
## 33 2.148899e-01 1.154232e+00 5.850129e-01 1.515711e-01 2.672983e-01
## 34 1.419427e-01 1.138079e+00 2.291256e-01 2.139171e-01 1.722849e-01
## 35 1.172845e-01 1.138781e+00 4.875288e-01 6.248792e-02 1.863383e-01
## 36 1.156248e-01 1.138588e+00 4.858716e-01 6.119835e-02 1.851006e-01
## 37 1.980357e-01 1.129245e+00 1.724678e-01 2.666896e-01 2.054726e-01
## 38 2.064729e-01 1.147047e+00 1.652023e-01 2.776184e-01 2.220802e-01
## 39 9.446426e-02 1.099504e+00 2.814514e-01 1.566435e-01 1.115080e-01
## 40 1.669170e-01 1.145625e+00 5.370942e-01 1.059263e-01 2.258682e-01
## 41 2.133883e-01 1.153933e+00 5.835129e-01 1.501203e-01 2.659682e-01
## 42 2.845177e-02 1.131873e+00 3.988580e-01 5.577994e-02 1.336349e-01
## 43 2.370981e-02 1.131053e+00 3.468302e-01 1.000002e-01 1.237360e-01
## 44 6.583423e-02 1.133937e+00 4.361643e-01 3.901174e-02 1.517613e-01
## 45 3.659609e-01 1.193590e+00 7.359596e-01 3.000935e-01 4.072596e-01
## 46 2.216077e-01 1.155591e+00 5.917238e-01 1.580729e-01 2.732708e-01
## 47 3.306479e-01 1.158177e+00 4.057136e-02 3.992737e-01 3.263223e-01
## 48 3.544616e-02 1.131200e+00 3.351296e-01 1.109050e-01 1.244480e-01
## 49 8.021818e-02 1.132878e+00 2.905208e-01 1.536343e-01 1.367164e-01
## 50 2.967439e-01 1.162523e+00 7.650796e-02 3.668893e-01 3.000169e-01
## 51 1.594089e-01 1.144454e+00 5.295954e-01 9.898200e-02 2.196252e-01
## 52 4.167418e-01 1.209440e+00 7.866601e-01 3.503495e-01 4.555144e-01
## 53 1.734767e-02 1.131497e+00 3.877794e-01 6.420236e-02 1.298462e-01
## 54 1.529283e-02 1.131023e+00 3.552229e-01 9.230533e-02 1.239093e-01
## 55 5.711044e-01 1.041679e+00 9.136360e-01 4.927627e-01 5.533294e-01
## 56 1.979065e-01 1.143822e+00 1.733967e-01 2.688691e-01 2.139518e-01
## 57 1.828099e-01 1.141722e+00 1.883778e-01 2.539578e-01 2.018575e-01
## 58 3.316212e-01 1.174394e+00 4.630814e-02 4.019135e-01 3.333798e-01
## 59 3.897497e-01 1.201403e+00 7.597333e-01 3.236961e-01 4.299848e-01
## 60 3.085855e+00 1.955312e+00 3.085906e+00 3.046869e+00 2.962497e+00
## 61 2.171423e-01 1.154684e+00 5.872630e-01 1.537490e-01 2.692970e-01
## 62 1.441781e-01 1.116649e+00 5.114217e-01 7.471482e-02 1.911196e-01
## 63 1.627424e-01 1.142848e+00 5.328079e-01 1.012438e-01 2.211900e-01
## 64 2.105431e-01 1.147732e+00 1.611867e-01 2.816489e-01 2.254716e-01
## 65 6.046001e-02 1.131920e+00 3.102012e-01 1.346140e-01 1.295498e-01
## 66 1.033961e-01 1.130900e+00 2.671798e-01 1.753446e-01 1.450866e-01
## 67 1.850155e-01 1.148644e+00 5.551712e-01 1.229384e-01 2.412136e-01
## 68 6.046001e-02 1.131920e+00 3.102012e-01 1.346140e-01 1.295498e-01
## 69 8.006011e-02 1.135045e+00 4.503645e-01 4.063510e-02 1.604193e-01
## 70 1.272031e-01 1.139979e+00 4.974329e-01 7.051805e-02 1.938669e-01
## 71 2.515340e-01 1.078718e+00 6.097268e-01 1.747447e-01 2.629674e-01
## 72 1.629150e-01 1.078402e+00 2.212419e-01 2.205202e-01 1.433113e-01
## 73 1.480677e-01 1.142777e+00 5.182689e-01 8.866692e-02 2.103519e-01
## 74 1.766381e-01 1.142457e+00 1.947068e-01 2.481136e-01 1.980032e-01
## 75 4.651864e-01 1.228897e+00 8.351279e-01 3.986885e-01 5.027000e-01
## 76 1.218684e-01 1.136022e+00 2.490749e-01 1.942124e-01 1.589702e-01
## 77 2.325142e-01 1.151671e+00 1.395643e-01 3.034243e-01 2.441372e-01
## 78 1.867568e-01 1.147995e+00 5.568624e-01 1.242894e-01 2.422152e-01
## 79 5.680787e-02 1.126769e+00 4.264191e-01 3.452293e-02 1.410308e-01
## 80 2.496859e-01 1.146814e+00 1.213518e-01 3.194140e-01 2.550731e-01
## 81 3.260098e-02 1.131154e+00 3.379659e-01 1.082455e-01 1.241739e-01
## 82 5.650837e-02 1.133307e+00 4.268562e-01 4.070375e-02 1.465581e-01
## 83 7.258640e-02 1.095218e+00 3.071326e-01 1.309741e-01 9.588010e-02
## 84 2.885364e-01 1.160090e+00 6.580046e-01 2.216250e-01 3.300632e-01
## 85 1.613057e-01 1.144745e+00 5.314898e-01 1.007287e-01 2.211949e-01
## 86 8.528896e-01 2.823401e-01 8.831900e-01 8.213557e-01 7.281699e-01
## 87 1.356596e-01 1.141068e+00 5.058775e-01 7.770970e-02 2.004500e-01
## 88 1.090437e-01 1.036543e+00 3.236332e-01 1.340052e-01 4.227879e-02
## 89 4.359095e-01 1.197086e+00 8.048818e-01 3.673368e-01 4.685665e-01
## 90 1.049174e+00 2.424546e-01 1.005845e+00 1.029135e+00 9.236579e-01
## 91 1.078796e-01 1.134797e+00 2.629879e-01 1.805292e-01 1.505807e-01
## 92 2.019680e-01 1.151723e+00 5.721048e-01 1.391222e-01 2.559140e-01
## 93 3.285784e-01 1.173579e+00 4.882950e-02 3.988852e-01 3.305562e-01
## 94 7.049716e-02 1.134281e+00 4.408186e-01 3.898339e-02 1.545084e-01
## 95 1.223031e-01 1.136063e+00 2.486427e-01 1.946383e-01 1.592435e-01
## 96 8.989968e-02 1.133473e+00 2.808814e-01 1.630184e-01 1.411078e-01
## 97 1.244765e-01 1.139641e+00 4.947102e-01 6.826109e-02 1.917756e-01
## 98 1.738719e-03 1.131106e+00 3.687403e-01 8.021938e-02 1.253810e-01
## 99 3.888408e-02 1.131267e+00 3.317027e-01 1.141306e-01 1.248648e-01
## 100 2.593004e-01 1.085832e+00 6.190626e-01 1.831540e-01 2.734389e-01
## 101 9.803765e-01 5.483165e-01 1.181062e+00 9.146970e-01 8.852085e-01
## 102 1.473960e-01 1.142681e+00 5.175980e-01 8.806384e-02 2.098090e-01
## 103 8.373513e-02 1.135360e+00 4.540332e-01 4.183777e-02 1.627832e-01
## 104 9.128275e-02 1.136044e+00 4.615680e-01 4.515319e-02 1.677861e-01
## 105 1.454597e-01 1.138475e+00 2.256328e-01 2.173763e-01 1.747506e-01
## 106 1.735202e-01 1.020969e+00 5.037204e-01 9.902023e-02 1.476056e-01
## 107 5.690354e-02 1.131784e+00 3.137447e-01 1.312135e-01 1.285403e-01
## 108 1.240023e-01 1.139583e+00 4.942367e-01 6.787210e-02 1.914135e-01
## 109 5.293475e-01 1.242733e+00 8.987697e-01 4.614364e-01 5.620356e-01
## 110 3.257332e-01 1.181352e+00 6.957598e-01 2.602581e-01 3.691356e-01
## 111 1.577097e-01 1.144196e+00 5.278984e-01 9.742200e-02 2.182234e-01
## 112 1.487395e-01 1.138854e+00 2.223762e-01 2.206039e-01 1.770820e-01
## 113 7.278911e-02 1.132477e+00 2.979194e-01 1.464598e-01 1.337247e-01
## 114 1.098153e-01 1.135024e+00 4.798789e-01 5.484530e-02 1.788047e-01
## 115 1.519909e-01 1.129433e+00 5.210184e-01 8.661841e-02 2.052148e-01
## 116 4.480867e-02 1.128043e+00 4.146778e-01 4.180683e-02 1.365114e-01
## 117 2.948710e-01 1.172812e+00 6.649211e-01 2.297894e-01 3.402158e-01
## 118 2.107407e-01 1.153411e+00 5.808680e-01 1.475649e-01 2.636274e-01
## 119 2.548804e-01 1.162872e+00 6.249647e-01 1.904973e-01 3.033123e-01
## 120 1.946575e-01 1.145138e+00 1.768736e-01 2.659249e-01 2.123703e-01
## 121 5.073899e-02 1.131575e+00 3.198874e-01 1.253399e-01 1.270075e-01
## 122 1.437605e-01 1.142168e+00 5.139673e-01 8.481802e-02 2.068840e-01
## 123 5.689958e-01 1.273085e+00 9.388905e-01 5.021043e-01 6.038569e-01
## 124 6.828126e-01 1.282772e+00 1.050572e+00 6.124806e-01 7.062524e-01
## 125 3.783295e-01 1.197600e+00 7.483202e-01 3.123618e-01 4.190605e-01
## 126 1.934720e-01 1.144954e+00 1.780457e-01 2.647522e-01 2.114079e-01
## 127 4.702175e-02 1.123522e+00 4.159981e-01 3.716451e-02 1.332873e-01
## 128 6.807085e-01 1.328080e+00 1.050563e+00 6.135419e-01 7.135668e-01
## 129 1.014170e+00 1.507789e+00 1.383272e+00 9.454006e-01 1.040116e+00
## 130 1.398879e-02 1.131024e+00 3.565233e-01 9.112458e-02 1.239872e-01
## 131 8.626488e-02 1.089467e+00 2.952959e-01 1.431516e-01 9.622689e-02
## 132 1.522565e-01 1.143383e+00 5.224521e-01 9.244868e-02 2.137537e-01
## 133 2.665997e-01 1.063746e+00 1.371697e-01 3.227368e-01 2.296646e-01
## 134 9.234970e-02 1.133637e+00 2.784425e-01 1.653985e-01 1.423020e-01
## 135 2.809217e-01 1.161770e+00 9.250682e-02 3.514867e-01 2.869187e-01
## 136 4.234176e-01 1.213171e+00 7.933815e-01 3.571426e-01 4.623303e-01
## 137 4.927688e-02 1.132871e+00 4.196390e-01 4.337186e-02 1.428124e-01
## 138 1.576307e-01 1.139930e+00 2.135516e-01 2.293610e-01 1.835482e-01
## 139 2.250851e-01 1.150294e+00 1.468639e-01 2.960582e-01 2.377626e-01
## 140 1.270814e+00 3.397715e-01 1.383764e+00 1.217762e+00 1.157299e+00
## 141 2.003972e-01 1.141615e+00 5.699115e-01 1.348977e-01 2.496378e-01
## 142 1.389942e-01 1.132555e+00 5.085248e-01 7.640374e-02 1.974909e-01
## 143 2.446862e-01 1.159853e+00 6.147486e-01 1.803776e-01 2.937355e-01
## 144 9.725084e-02 1.129161e+00 2.732564e-01 1.690106e-01 1.406230e-01
## 145 1.920608e-01 1.127254e+00 5.602364e-01 1.233653e-01 2.354918e-01
## 146 3.996512e-01 1.076799e+00 7.547950e-01 3.226927e-01 4.004117e-01
## 147 1.197174e-02 1.121119e+00 3.762808e-01 6.836811e-02 1.171170e-01
## 148 1.280141e-01 1.132702e+00 2.426266e-01 1.994518e-01 1.598981e-01
## 149 3.429644e-01 1.116600e+00 7.064468e-01 2.690499e-01 3.614485e-01
## 150 3.830923e-02 1.095704e+00 3.834954e-01 5.462736e-02 9.506243e-02
## 151 1.522654e-01 1.121542e+00 2.184688e-01 2.206519e-01 1.670961e-01
## 152 4.771994e-01 1.233644e+00 8.471349e-01 4.106458e-01 5.143519e-01
## 153 5.413872e-02 1.085390e+00 3.977548e-01 4.135995e-02 9.189169e-02
## 154 3.742198e-02 1.131237e+00 3.331601e-01 1.127573e-01 1.246761e-01
## 155 2.460683e-01 1.160855e+00 6.161607e-01 1.818800e-01 2.952885e-01
## 156 2.657941e-01 8.654854e-01 4.437078e-01 2.357366e-01 1.444460e-01
## 157 1.698412e-01 1.141517e+00 2.014420e-01 2.414033e-01 1.927435e-01
## 158 1.255434e-01 1.136372e+00 2.454213e-01 1.978142e-01 1.613031e-01
## 159 5.559950e-02 1.131737e+00 3.150440e-01 1.299688e-01 1.281928e-01
## 160 2.959774e-02 1.131112e+00 3.409599e-01 1.054487e-01 1.239549e-01
## 161 2.495457e-01 1.155003e+00 1.228882e-01 3.203226e-01 2.589635e-01
## 162 3.153009e-01 1.170105e+00 6.039656e-02 3.856732e-01 3.182827e-01
## 163 1.708687e-01 1.146261e+00 5.410410e-01 1.096110e-01 2.291844e-01
## 164 1.723703e-01 1.146506e+00 5.425408e-01 1.110160e-01 2.304499e-01
## 165 1.517823e-01 1.143314e+00 5.219785e-01 9.201878e-02 2.133672e-01
## 166 8.033673e-02 1.135069e+00 4.506407e-01 4.071531e-02 1.605955e-01
## 167 3.657181e-01 7.654198e-01 4.994905e-01 3.344407e-01 2.427500e-01
## 168 1.583300e-01 1.092703e+00 5.200098e-01 8.239686e-02 1.867586e-01
## 169 2.846395e-02 1.125255e+00 3.422895e-01 1.017904e-01 1.180308e-01
## 170 4.261047e-01 1.214146e+00 7.960671e-01 3.598138e-01 4.649200e-01
## 171 2.491089e-01 9.862399e-01 2.234820e-01 2.860510e-01 1.724552e-01
## 172 2.740200e-02 1.121214e+00 3.951346e-01 5.161435e-02 1.226789e-01
## 173 2.810983e-01 1.147434e+00 6.497419e-01 2.124573e-01 3.188158e-01
## 174 7.721099e-02 1.063848e+00 4.074683e-01 4.395449e-02 8.004192e-02
## 175 1.937513e-01 1.073827e+00 1.937656e-01 2.510009e-01 1.674738e-01
## 176 8.361475e-02 1.058057e+00 3.324986e-01 1.140017e-01 5.366714e-02
## 177 1.655245e-01 9.791470e-01 4.471345e-01 1.161623e-01 8.665411e-02
## 178 1.932349e-01 1.144917e+00 1.782802e-01 2.645177e-01 2.112157e-01
## 179 1.822424e-01 1.120001e+00 1.887988e-01 2.496406e-01 1.878073e-01
## 180 5.440610e-01 1.261833e+00 9.139659e-01 4.772484e-01 5.794736e-01
## 181 1.068522e-01 1.134713e+00 2.640100e-01 1.795261e-01 1.499974e-01
## 182 1.086699e-01 1.137809e+00 4.789273e-01 5.600680e-02 1.799877e-01
## 183 1.806099e-01 1.135752e+00 5.498997e-01 1.149326e-01 2.309359e-01
## 184 4.188833e-01 9.910397e-01 7.533218e-01 3.401964e-01 3.926961e-01
## 185 2.914420e-01 1.169704e+00 6.613981e-01 2.260205e-01 3.361841e-01
## 186 2.985389e-01 1.144272e+00 6.665320e-01 2.287676e-01 3.324727e-01
## 187 4.303480e-02 1.111696e+00 3.312615e-01 1.084759e-01 1.054258e-01
## 188 2.769938e-01 9.816410e-01 2.088169e-01 3.154332e-01 2.017129e-01
## 189 2.916017e-01 1.151621e+00 7.938935e-02 3.606547e-01 2.911641e-01
## 190 1.762535e+00 6.785080e-01 1.833566e+00 1.714146e+00 1.644539e+00
## 191 1.617584e-01 1.138229e+00 5.315144e-01 9.865046e-02 2.178142e-01
## 192 2.058406e-01 1.146942e+00 1.658264e-01 2.769924e-01 2.215554e-01
## 193 1.143998e-01 1.138448e+00 4.846485e-01 6.025815e-02 1.841913e-01
## 194 1.945077e-01 1.126750e+00 1.760763e-01 2.628313e-01 2.012987e-01
## 195 3.374182e-01 1.107476e+00 5.796224e-02 3.997916e-01 3.129675e-01
## 196 4.383826e-01 1.140793e+00 7.641395e-02 5.021873e-01 4.143945e-01
## 197 2.951266e-01 8.401757e-01 4.176211e-01 2.774509e-01 1.694871e-01
## 198 1.306410e-01 1.136878e+00 2.403543e-01 2.028146e-01 1.646203e-01
## 199 4.896075e-02 1.131520e+00 3.216595e-01 1.236508e-01 1.266176e-01
## 200 2.882322e-01 1.171073e+00 6.582878e-01 2.232494e-01 3.340404e-01
## 201 2.070656e-02 1.131600e+00 3.911304e-01 6.156499e-02 1.309045e-01
## 202 2.210503e-02 1.129485e+00 3.483695e-01 9.786849e-02 1.221677e-01
## 203 1.161407e-01 1.095117e+00 2.607918e-01 1.774707e-01 1.208105e-01
## 204 3.093295e-01 8.877535e-01 3.036612e-01 3.246129e-01 2.006525e-01
## 205 3.284006e-01 8.051818e-01 4.466179e-01 3.063999e-01 2.030876e-01
## 206 4.644782e-01 1.215336e+00 9.817318e-02 5.341770e-01 4.589458e-01
## 207 2.785679e-01 1.111322e+00 9.838145e-02 3.425948e-01 2.624633e-01
## 208 3.271953e-02 1.132047e+00 4.031164e-01 5.280732e-02 1.353054e-01
## 209 2.070656e-02 1.131600e+00 3.911304e-01 6.156499e-02 1.309045e-01
## 210 2.805966e-01 1.026630e+00 1.602024e-01 3.296373e-01 2.261540e-01
## 211 2.490988e-01 1.126039e+00 6.160898e-01 1.781264e-01 2.825591e-01
## 212 8.373513e-02 1.135360e+00 4.540332e-01 4.183777e-02 1.627832e-01
## 213 1.306446e-01 1.054449e+00 4.737707e-01 5.475540e-02 1.295030e-01
## 214 1.993204e-01 1.145878e+00 1.722652e-01 2.705384e-01 2.161773e-01
## 215 5.251430e-02 1.124437e+00 4.217084e-01 3.457466e-02 1.367819e-01
## 216 5.284125e-01 1.254973e+00 8.983242e-01 4.616539e-01 5.641959e-01
## 217 1.467637e-01 1.142591e+00 5.169666e-01 8.749714e-02 2.092987e-01
## 218 3.553519e-01 1.134406e+00 2.736264e-02 4.206253e-01 3.387125e-01
## 219 1.110409e-01 1.135059e+00 2.598430e-01 1.836174e-01 1.524047e-01
## 220 7.325144e-01 4.491635e-01 8.665170e-01 6.824485e-01 6.181638e-01
## 221 3.499018e-01 1.094825e+00 7.096821e-01 2.741916e-01 3.601592e-01
## 222 1.379831e-01 1.104824e+00 2.355142e-01 2.025809e-01 1.444156e-01
## 223 1.405596e-01 1.137926e+00 2.304994e-01 2.125573e-01 1.713253e-01
## 224 4.410024e-02 1.132588e+00 4.144729e-01 4.589043e-02 1.402987e-01
## 225 5.634005e-01 5.705177e-01 6.696601e-01 5.248169e-01 4.420884e-01
## 226 1.729962e-01 1.133868e+00 1.975787e-01 2.431656e-01 1.899701e-01
## 26 27 28 29 30
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27 2.210544e-01
## 28 1.439185e-01 7.713590e-02
## 29 3.524643e-01 1.314402e-01 2.085582e-01
## 30 4.628154e-01 2.417610e-01 3.188969e-01 1.104268e-01
## 31 5.777375e-01 3.608761e-01 4.360709e-01 2.343827e-01 1.396653e-01
## 32 1.746988e-01 7.751473e-02 5.882430e-02 1.933176e-01 3.018147e-01
## 33 4.211652e-01 2.001108e-01 2.772467e-01 6.881143e-02 4.165023e-02
## 34 6.433261e-02 1.567218e-01 7.958592e-02 2.881357e-01 3.984828e-01
## 35 3.235598e-01 1.025054e-01 1.796413e-01 2.910583e-02 1.392556e-01
## 36 3.219001e-01 1.008457e-01 1.779816e-01 3.075368e-02 1.409153e-01
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## 38 1.975817e-04 2.212520e-01 1.441161e-01 3.526619e-01 4.630130e-01
## 39 1.228908e-01 1.083873e-01 4.262625e-02 2.362907e-01 3.463668e-01
## 40 3.731924e-01 1.521379e-01 2.292738e-01 2.105047e-02 8.962307e-02
## 41 4.196636e-01 1.986091e-01 2.757450e-01 6.731187e-02 4.315185e-02
## 42 2.347271e-01 1.367265e-02 9.080856e-02 1.177732e-01 2.280883e-01
## 43 1.825655e-01 3.848892e-02 3.864698e-02 1.699182e-01 2.802499e-01
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## 47 1.250504e-01 3.454095e-01 2.683863e-01 4.765834e-01 5.870089e-01
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## 49 1.260571e-01 9.499729e-02 1.786139e-02 2.264172e-01 3.367583e-01
## 50 9.050436e-02 3.115223e-01 2.343913e-01 4.428995e-01 5.532767e-01
## 51 3.656842e-01 1.446298e-01 2.217657e-01 1.371009e-02 9.713117e-02
## 52 6.230163e-01 4.019628e-01 4.790983e-01 2.705769e-01 1.602056e-01
## 53 2.236230e-01 2.568562e-03 7.970447e-02 1.288727e-01 2.391924e-01
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## 55 7.635696e-01 5.576939e-01 6.283629e-01 4.404191e-01 3.541425e-01
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## 57 2.352983e-02 1.975885e-01 1.204570e-01 3.289792e-01 4.393458e-01
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## 59 5.960250e-01 3.749706e-01 4.521065e-01 2.436049e-01 1.332096e-01
## 60 3.095205e+00 3.085713e+00 3.087231e+00 3.084002e+00 3.093438e+00
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## 64 4.267765e-03 2.253222e-01 1.481863e-01 3.567319e-01 4.670832e-01
## 65 1.458153e-01 7.523912e-02 1.896785e-03 2.066617e-01 3.170001e-01
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## 67 3.912908e-01 1.702364e-01 2.473723e-01 3.900798e-02 7.152458e-02
## 68 1.458153e-01 7.523912e-02 1.896785e-03 2.066617e-01 3.170001e-01
## 69 2.863354e-01 6.528100e-02 1.424169e-01 6.620699e-02 1.764800e-01
## 70 3.334784e-01 1.124240e-01 1.895599e-01 1.930030e-02 1.293370e-01
## 71 4.515108e-01 2.376199e-01 3.111206e-01 1.207671e-01 8.454572e-02
## 72 8.245584e-02 1.766996e-01 1.076982e-01 3.026959e-01 4.120984e-01
## 73 3.543431e-01 1.332886e-01 2.104245e-01 4.039849e-03 1.084724e-01
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## 75 6.714617e-01 4.504073e-01 5.275432e-01 3.190354e-01 2.086463e-01
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## 77 2.623885e-02 2.472933e-01 1.701574e-01 3.787019e-01 4.890543e-01
## 78 3.930308e-01 1.719779e-01 2.491129e-01 4.066633e-02 6.979259e-02
## 79 2.627862e-01 4.216165e-02 1.189664e-01 8.979109e-02 2.002178e-01
## 80 4.407141e-02 2.644571e-01 1.873757e-01 3.957457e-01 5.061549e-01
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## 84 4.947179e-01 2.737695e-01 3.508532e-01 1.423558e-01 3.375354e-02
## 85 3.675810e-01 1.465266e-01 2.236625e-01 1.554939e-02 9.523439e-02
## 86 8.648761e-01 8.539393e-01 8.512759e-01 8.707972e-01 9.058388e-01
## 87 3.419349e-01 1.208805e-01 1.980164e-01 1.110005e-02 1.208805e-01
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## 89 6.420056e-01 4.211499e-01 4.981964e-01 2.897705e-01 1.801655e-01
## 90 1.023421e+00 1.052548e+00 1.037139e+00 1.087575e+00 1.133965e+00
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## 93 1.223031e-01 3.433575e-01 2.662216e-01 4.747628e-01 5.851185e-01
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## 111 3.639850e-01 1.429306e-01 2.200665e-01 1.207749e-02 9.883038e-02
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## 212 2.900104e-01 6.895602e-02 1.460919e-01 6.253763e-02 1.728050e-01
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## 215 2.582244e-01 3.801162e-02 1.144859e-01 9.449897e-02 2.049146e-01
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## 221 5.513400e-01 3.356948e-01 4.102897e-01 2.112852e-01 1.240119e-01
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## 226 3.444414e-02 1.877603e-01 1.107472e-01 3.190086e-01 4.294221e-01
## 31 32 33 34 35
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32 4.063782e-01
## 33 1.739175e-01 2.609586e-01
## 34 5.142570e-01 1.153429e-01 3.568326e-01
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## 226 5.434247e-01 1.403888e-01 3.877801e-01 3.191574e-02 2.902034e-01
## 36 37 38 39 40
## 2
## 3
## 4
## 5
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## 37 3.134057e-01
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## 41 42 43 44 45
## 2
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## 42 1.849365e-01
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## 46 47 48 49 50
## 2
## 3
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## 46
## 47 5.520911e-01
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## 51 52 53 54 55
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## 226 3.323134e-01 5.895825e-01 1.903265e-01 1.577219e-01 7.292338e-01
## 56 57 58 59 60
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## 57 1.509676e-02
## 58 1.337361e-01 1.488276e-01
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## 61 62 63 64 65
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## 226 3.900321e-01 3.151876e-01 3.355867e-01 3.860440e-02 1.126389e-01
## 66 67 68 69 70
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## 67 2.883726e-01
## 68 4.302165e-02 2.454755e-01
## 69 1.834296e-01 1.049554e-01 1.405201e-01
## 70 2.305656e-01 5.781241e-02 1.876631e-01 4.714300e-02
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## 72 7.478321e-02 3.415315e-01 1.092646e-01 2.390142e-01 2.848424e-01
## 73 2.514280e-01 3.694778e-02 2.085277e-01 6.800763e-02 2.086463e-02
## 74 7.338856e-02 3.616536e-01 1.161781e-01 2.566982e-01 3.038412e-01
## 75 5.685327e-01 2.801709e-01 5.256464e-01 3.851263e-01 3.379833e-01
## 76 1.886943e-02 3.068839e-01 6.140840e-02 2.019285e-01 2.490715e-01
## 77 1.292276e-01 4.175297e-01 1.720542e-01 3.125743e-01 3.597173e-01
## 78 2.901009e-01 1.990620e-03 2.472161e-01 1.066985e-01 5.955902e-02
## 79 1.597928e-01 1.287527e-01 1.170726e-01 2.452095e-02 7.107595e-02
## 80 1.462898e-01 4.346417e-01 1.892706e-01 3.297119e-01 3.768417e-01
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## 88 1.044293e-01 2.565492e-01 9.544394e-02 1.637776e-01 2.039922e-01
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## 90 1.027690e+00 1.105004e+00 1.037452e+00 1.069769e+00 1.084481e+00
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## 95 1.929654e-02 3.073186e-01 6.184308e-02 2.023632e-01 2.495062e-01
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## 97 2.278393e-01 6.053904e-02 1.849365e-01 4.441637e-02 2.726628e-03
## 98 1.016584e-01 1.867542e-01 5.872129e-02 8.179883e-02 1.289418e-01
## 99 6.454865e-02 2.238996e-01 2.157592e-02 1.189442e-01 1.660872e-01
## 100 3.584951e-01 9.951258e-02 3.175121e-01 1.844569e-01 1.430530e-01
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## 103 1.871040e-01 1.012804e-01 1.441951e-01 3.675020e-03 4.346798e-02
## 104 1.946503e-01 9.373277e-02 1.517428e-01 1.122264e-02 3.592036e-02
## 105 4.227344e-02 3.304752e-01 8.499966e-02 2.255198e-01 2.726628e-01
## 106 2.566867e-01 1.337896e-01 2.212252e-01 1.281529e-01 1.198370e-01
## 107 4.656694e-02 2.419191e-01 3.556471e-03 1.369636e-01 1.841066e-01
## 108 2.273652e-01 6.101323e-02 1.844623e-01 4.394217e-02 3.200824e-03
## 109 6.325844e-01 3.444310e-01 5.897887e-01 4.493202e-01 4.022027e-01
## 110 4.290831e-01 1.407177e-01 3.861932e-01 2.456731e-01 1.985301e-01
## 111 2.610691e-01 2.730579e-02 2.181697e-01 7.764962e-02 3.050662e-02
## 112 4.554257e-02 3.337550e-01 8.827951e-02 2.287996e-01 2.759426e-01
## 113 3.075132e-02 2.578046e-01 1.232910e-02 1.528492e-01 1.999922e-01
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## 150 1.215386e-01 1.748311e-01 8.246331e-02 7.520846e-02 1.188257e-01
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## 179 7.989125e-02 3.665042e-01 1.225222e-01 2.618459e-01 3.088305e-01
## 180 6.474060e-01 3.590455e-01 6.045210e-01 4.640009e-01 4.168579e-01
## 181 4.994607e-03 2.918677e-01 4.639219e-02 1.869123e-01 2.340553e-01
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## 183 2.836631e-01 1.315690e-02 2.409657e-01 1.008799e-01 5.438706e-02
## 184 5.089888e-01 2.764536e-01 4.718774e-01 3.524277e-01 3.162578e-01
## 185 3.947703e-01 1.064420e-01 3.519004e-01 2.113853e-01 1.642458e-01
## 186 4.012281e-01 1.159966e-01 3.587405e-01 2.190402e-01 1.724710e-01
## 187 6.694867e-02 2.242016e-01 2.953708e-02 1.199965e-01 1.666860e-01
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## 189 1.882138e-01 4.765057e-01 2.312169e-01 3.716000e-01 4.187176e-01
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## 193 2.177639e-01 7.061571e-02 1.748598e-01 3.433970e-02 1.280330e-02
## 194 9.151755e-02 3.790951e-01 1.344429e-01 2.743118e-01 3.213636e-01
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## 211 3.513281e-01 7.118420e-02 3.090514e-01 1.702636e-01 1.245750e-01
## 212 1.871040e-01 1.012804e-01 1.441951e-01 3.675020e-03 4.346798e-02
## 213 2.191346e-01 1.181866e-01 1.814455e-01 8.557955e-02 8.707930e-02
## 214 9.605069e-02 3.843360e-01 1.388604e-01 2.793806e-01 3.265235e-01
## 215 1.552233e-01 1.334867e-01 1.125946e-01 2.953298e-02 7.588566e-02
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## 217 2.501241e-01 3.825182e-02 2.072237e-01 6.670359e-02 1.956059e-02
## 218 2.526899e-01 5.392632e-01 2.955517e-01 4.348192e-01 4.817050e-01
## 219 8.482614e-03 2.960564e-01 5.058092e-02 1.911010e-01 2.382440e-01
## 220 7.578819e-01 7.163568e-01 7.477091e-01 7.197530e-01 7.163297e-01
## 221 4.495362e-01 1.788644e-01 4.084441e-01 2.736672e-01 2.299962e-01
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## 224 1.474781e-01 1.409153e-01 1.045602e-01 3.595987e-02 8.310287e-02
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## 226 6.962093e-02 3.579129e-01 1.126389e-01 2.529958e-01 3.001183e-01
## 71 72 73 74 75
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## 72 3.892227e-01
## 73 1.217227e-01 3.052530e-01
## 74 4.224060e-01 6.633579e-02 3.247058e-01
## 75 2.419988e-01 6.192079e-01 3.171187e-01 6.418245e-01
## 76 3.688436e-01 6.775615e-02 2.699361e-01 5.476965e-02 5.870548e-01
## 77 4.773330e-01 1.019244e-01 3.805819e-01 5.587611e-02 6.977006e-01
## 78 9.603590e-02 3.430708e-01 3.869864e-02 3.633936e-01 2.784338e-01
## 79 1.964596e-01 2.144950e-01 9.187198e-02 2.331593e-01 4.088095e-01
## 80 4.927915e-01 1.118128e-01 3.977014e-01 7.338588e-02 7.147811e-01
## 81 2.825376e-01 1.332634e-01 1.806687e-01 1.440371e-01 4.977874e-01
## 82 1.990074e-01 2.163310e-01 9.155937e-02 2.331464e-01 4.086780e-01
## 83 3.036474e-01 9.173052e-02 2.138163e-01 1.198784e-01 5.290237e-01
## 84 8.722995e-02 4.421147e-01 1.407059e-01 4.650890e-01 1.772420e-01
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## 90 1.051631e+00 9.653557e-01 1.091579e+00 1.024610e+00 1.238341e+00
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## 100 1.096567e-02 3.987770e-01 1.260223e-01 4.311106e-01 2.311127e-01
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## 110 1.206218e-01 4.806346e-01 1.776655e-01 5.023713e-01 1.394532e-01
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## 139 4.700172e-01 9.608594e-02 3.731528e-01 4.844704e-02 6.902715e-01
## 140 1.152518e+00 1.258540e+00 1.243161e+00 1.324860e+00 1.242612e+00
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## 226 4.171227e-01 5.735522e-02 3.209757e-01 8.990414e-03 6.380432e-01
## 76 77 78 79 80
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## 77 1.106458e-01
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## 82 8.910936e-02
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## 180 6.519406e-01 3.420930e-01 8.726394e-01 4.735639e-01 6.663641e-01
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## 183 2.883341e-01 2.497894e-02 5.089202e-01 1.103783e-01 3.027452e-01
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## 186 4.060111e-01 9.972765e-02 6.263130e-01 2.285155e-01 4.203959e-01
## 187 7.224798e-02 2.410940e-01 2.909061e-01 1.105725e-01 8.622108e-02
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## 190 1.783171e+00 1.741299e+00 1.844426e+00 1.752510e+00 1.786406e+00
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## 193 2.222794e-01 8.756822e-02 4.429782e-01 4.390266e-02 2.367029e-01
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## 195 2.328887e-01 5.366910e-01 6.925774e-02 4.066726e-01 2.191594e-01
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## 199 5.891887e-02 2.509288e-01 2.796176e-01 1.194579e-01 7.334233e-02
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## 201 1.285862e-01 1.812615e-01 3.492850e-01 4.979059e-02 1.430096e-01
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## 220 7.627745e-01 7.172488e-01 8.642388e-01 7.208217e-01 7.678792e-01
## 221 4.547110e-01 1.647109e-01 6.721621e-01 2.826620e-01 4.688295e-01
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## 226 6.543269e-02 3.748612e-01 1.559856e-01 2.434380e-01 5.115247e-02
## 96 97 98 99 100
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## 97 2.143762e-01
## 98 8.816096e-02 1.262152e-01
## 99 5.101560e-02 1.633606e-01 3.714536e-02
## 100 3.461362e-01 1.453525e-01 2.609602e-01 2.966353e-01
## 101 1.025937e+00 9.280387e-01 9.811997e-01 9.993456e-01 8.155522e-01
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## 103 1.736348e-01 4.074135e-02 8.547385e-02 1.226192e-01 1.811285e-01
## 104 1.811824e-01 3.319373e-02 9.302147e-02 1.301668e-01 1.743363e-01
## 105 5.555998e-02 2.699361e-01 1.437209e-01 1.065756e-01 4.004792e-01
## 106 2.464888e-01 1.198294e-01 1.747819e-01 2.034243e-01 1.290873e-01
## 107 3.299615e-02 1.813800e-01 5.516482e-02 1.801945e-02 3.140643e-01
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## 109 6.192205e-01 4.049277e-01 5.310857e-01 5.682190e-01 2.887858e-01
## 110 4.156329e-01 2.012567e-01 3.274719e-01 3.646173e-01 1.101480e-01
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## 123 6.588955e-01 4.445194e-01 5.707346e-01 6.078799e-01 3.307497e-01
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## 175 1.146185e-01 3.130687e-01 1.921310e-01 1.581179e-01 4.281858e-01
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## 181 1.695251e-02 2.313287e-01 1.051135e-01 6.796811e-02 3.626783e-01
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## 180 4.353712e-01 6.009646e-01 4.200587e-01 2.041802e-02 2.183278e-01
## 181 2.614333e-01 4.994866e-02 2.308545e-01 6.361688e-01 4.325854e-01
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## 189 4.303045e-01 2.347678e-01 4.155183e-01 8.204785e-01 6.171834e-01
## 190 1.627338e+00 1.772632e+00 1.746762e+00 1.742511e+00 1.739782e+00
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## 193 1.203384e-01 1.713034e-01 9.602472e-03 4.149985e-01 2.113334e-01
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## 219 2.651631e-01 5.413739e-02 2.350432e-01 6.403565e-01 4.367741e-01
## 220 5.967030e-01 7.466883e-01 7.164645e-01 7.949460e-01 7.356618e-01
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## 223 2.918010e-01 8.365610e-02 2.645619e-01 6.698685e-01 4.662929e-01
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## 226 3.185333e-01 1.161864e-01 2.969186e-01 7.019925e-01 4.986045e-01
## 111 112 113 114 115
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## 112 3.064492e-01
## 113 2.304988e-01 7.595041e-02
## 114 4.802242e-02 2.585325e-01 1.825889e-01
## 115 1.534954e-02 3.004121e-01 2.245716e-01 4.301346e-02
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## 117 1.371612e-01 4.436105e-01 3.676601e-01 1.851176e-01 1.442015e-01
## 118 5.303093e-02 3.594802e-01 2.835298e-01 1.010066e-01 6.101367e-02
## 119 9.717069e-02 4.036199e-01 3.276695e-01 1.451335e-01 1.044709e-01
## 120 3.523672e-01 4.591799e-02 1.218684e-01 3.044480e-01 3.462870e-01
## 121 2.084487e-01 9.800053e-02 2.205012e-02 1.605420e-01 2.025688e-01
## 122 1.394927e-02 2.925000e-01 2.165496e-01 3.410960e-02 1.589643e-02
## 123 4.112861e-01 7.177354e-01 6.417849e-01 4.592287e-01 4.178818e-01
## 124 5.257345e-01 8.311757e-01 7.553990e-01 5.731734e-01 5.308396e-01
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## 130 1.716985e-01 1.347507e-01 5.880032e-02 1.237997e-01 1.659254e-01
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## 135 4.386314e-01 1.321822e-01 2.081326e-01 3.907090e-01 4.324949e-01
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## 137 1.084328e-01 1.980164e-01 1.220660e-01 6.057014e-02 1.030221e-01
## 138 3.153404e-01 8.891177e-03 8.484159e-02 2.674231e-01 3.092939e-01
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## 141 4.359003e-02 3.490315e-01 2.731205e-01 9.064615e-02 4.896835e-02
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## 143 8.697836e-02 3.934254e-01 3.174751e-01 1.349270e-01 9.427474e-02
## 144 2.548865e-01 5.183322e-02 2.481527e-02 2.069163e-01 2.486470e-01
## 145 4.009190e-02 3.402084e-01 2.644773e-01 8.332809e-02 4.033097e-02
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## 147 1.516459e-01 1.554706e-01 7.983431e-02 1.036247e-01 1.449971e-01
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## 149 1.914765e-01 4.894509e-01 4.144505e-01 2.357997e-01 1.928153e-01
## 150 1.482060e-01 1.664847e-01 9.372862e-02 1.013555e-01 1.391859e-01
## 151 3.094474e-01 1.790862e-02 8.041981e-02 2.614253e-01 3.026001e-01
## 152 3.194896e-01 6.259389e-01 5.499885e-01 3.674346e-01 3.261511e-01
## 153 1.380343e-01 1.825011e-01 1.107595e-01 9.288724e-02 1.278141e-01
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## 176 2.111334e-01 1.308605e-01 8.013680e-02 1.657464e-01 2.006156e-01
## 177 1.835729e-01 2.589154e-01 2.031457e-01 1.600812e-01 1.683898e-01
## 178 3.509446e-01 4.449540e-02 1.204458e-01 3.030254e-01 3.448655e-01
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## 180 3.863513e-01 6.928005e-01 6.168501e-01 4.342945e-01 3.929618e-01
## 181 2.645619e-01 4.188732e-02 3.406309e-02 2.166483e-01 2.585774e-01
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## 226 1.223366e-01 3.166699e-01 7.418454e-01 8.547217e-01 5.511944e-01
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## 127 2.397637e-01
## 128 8.741806e-01 6.346595e-01
## 129 1.207575e+00 9.678414e-01 3.343121e-01
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## 133 1.090205e-01 3.075725e-01 9.350885e-01 1.265091e+00 2.535449e-01
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## [ reached getOption("max.print") -- omitted 219 rows ]cc <- hclust(dc, method = "complete")
plot(cc,cex = 0.3, hang = -1)